Skin information processing method, skin information processing device, and non-transitory computer-readable medium

ABSTRACT

A skin information processing method for a skin information processing device that includes a storage portion includes include acquiring an image, and determining a base point that represents a sweat pore on a ridge of skin, from the acquired image and acquiring position information corresponding to a position of the base point on the image. The skin information processing method includes acquiring sample information indicating changes in color information around the determined base point, generating, as frequency information, information associating frequency components of the acquired sample information with the position information. The skin information processing method includes causing the storage portion to store information including the generated frequency information and the position information of the base point, as information used in skin authentication.

CROSS REFERENCE TO RELATED APPLICATION

This application is a Continuation Application of InternationalApplication No. PCT/JP2017/039417, filed Oct. 31, 2017, which claimspriority from Japanese Patent Application No. 2016-213899, filed on Oct.31, 2016. This disclosure of the foregoing application is herebyincorporated by reference in its entirety.

BACKGROUND

The present disclosure relates to a skin information processing method,a skin information processing device, and a non-transitorycomputer-readable medium that are configured to analyze an image andgenerate collation information used for collation of biometricinformation.

Recently, various types of fingerprint authentication devices that canbe installed in mobile devices, such as a smart phone and a notebookpersonal computer, have been proposed. For example, a known personalidentification device that uses, as collation information used forcollation, information obtained by performing frequency spectrumconversion on a fingerprint image. Thus, the personal identificationdevice is unlikely to be affected by disturbance, such as inclination ofa finger with respect to a fingerprint sensor.

SUMMARY

In accordance with miniaturization of a fingerprint sensor that isinstalled in a mobile device, an image of an acquired finger printbecomes smaller than in related art. When a user performs an inputoperation of a fingerprint, in many cases, the user causes a finger ofthe hand that is holding the mobile device to touch the fingerprintsensor installed in the mobile device. In this case, since the user hasto move the finger in an unnatural direction, the input operation of thefingerprint tends to become unstable. More specifically, an imageacquired under conditions in which a position and an angle are differentfrom those at the time of registration tends to be acquired.Accordingly, even when the size of the image is smaller than in therelated art, a technology is required that generates collationinformation that is unlikely to be affected by acquisition conditions ofbiometric information.

Various embodiments of the broad principles derived herein provide askin information processing method, a skin information processingdevice, and a non-transitory computer-readable medium that are capableof generating collation information that is unlikely to be affected byacquisition conditions of biometric information even when a size of animage representing the biometric information is smaller than in relatedart.

Embodiments provide a skin information processing method for a skininformation processing device including a storage portion includesacquiring an image, determining a base point that represents a sweatpore on a ridge of skin, from the acquired image and acquiring positioninformation corresponding to a position of the base point on the image,acquiring sample information indicating changes in color informationaround the determined base point, generating, as frequency information,information associating frequency components of the acquired sampleinformation with the position information, and causing the storageportion to store information including the generated frequencyinformation and the position information of the base point, asinformation used in skin authentication.

Embodiments also provide a skin information processing device thatincludes a processor, and a memory. The memory is configured to storecomputer-readable instructions that, when executed by the processor,instruct the processor to perform processes. The processes includeacquiring an image, determining a base point that represents a sweatpore on a ridge of skin, from the acquired image and acquiring positioninformation corresponding to a position of the base point on the image,acquiring sample information indicating changes in color informationaround the determined base point, generating, as frequency information,information associating frequency components of the acquired sampleinformation with the position information, and causing the storageportion to store information including the generated frequencyinformation and the position information of the base point, asinformation used in skin authentication.

Embodiments further provide a non-transitory computer-readable mediumthat stores computer-readable instructions that are executed by aprocessor provided in a skin information processing device including astorage portion, the computer-readable instructions, when executed,instructing the processor to perform processes. The processes includeacquiring an image, determining a base point that represents a sweatpore on a ridge of skin, from the acquired image and acquiring positioninformation corresponding to a position of the base point on the image,acquiring sample information indicating changes in color informationaround the determined base point, generating, as frequency information,information associating frequency components of the acquired sampleinformation with the position information, and causing the storageportion to store information including the generated frequencyinformation and the position information of the base point, asinformation used in skin authentication.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the disclosure will be described below in detail withreference to the accompanying drawings in which:

FIG. 1 is a block diagram of a skin information processing device;

FIG. 2 is a functional block diagram of the skin information processingdevice;

FIG. 3 is a flowchart of frequency information storage processing of afirst embodiment;

FIG. 4 is an explanatory diagram of a process to generate frequencyinformation on the basis of an image;

FIG. 5 is a graph showing changes in color information with respect tosecond position information, on the basis of a plurality of pieces ofsample data;

FIG. 6 is a graph showing frequency information generated for theplurality of pieces of sample data;

FIG. 7 is an explanatory diagram of frequency information generated onthe basis of the image;

FIG. 8 is a flowchart of skin information processing of a secondembodiment;

FIG. 9 is a flowchart of image analysis processing that is performed inthe skin information processing shown in FIG. 8;

FIG. 10 is a flowchart of connection information generation processingperformed in the image analysis processing shown in FIG. 9;

FIG. 11 is an explanatory diagram of a process that generates connectioninformation;

FIG. 12 is a flowchart of deletion processing that is performed in theconnection information generation processing shown in FIG. 10;

FIG. 13 is a flowchart of list correction processing that is performedin the connection information generation processing shown in FIG. 10;

FIG. 14 is a flowchart of ridge information generation processing thatis performed in the image analysis processing shown in FIG. 9;

FIG. 15 is an explanatory diagram of the registration image;

FIG. 16 is an explanatory diagram of a process that generates the ridgeinformation;

FIG. 17 is a flowchart of angle calculation processing that is performedin the ridge information generation processing shown in FIG. 14;

FIG. 18 is an explanatory diagram of a branch point list;

FIG. 19 is a flowchart of branch point processing that is performed inthe ridge information generation processing shown in FIG. 14;

FIG. 20 is a flowchart of frequency information generation processingthat is performed in the image analysis processing shown in FIG. 9;

FIG. 21 is an explanatory diagram of a process to acquire samples;

FIG. 22 is an explanatory diagram of the ridge information;

FIG. 23 is an explanatory diagram of a collation image;

FIG. 24 is an explanatory diagram of the ridge information;

FIG. 25 is a flowchart of collation processing that is performed in theskin information processing shown in FIG. 8;

FIG. 26 is a flowchart of pair range candidate selection processing thatis performed in the collation processing shown in FIG. 25;

FIG. 27 is an explanatory diagram of an image represented byregistration ridge information, and an image represented by collationridge information;

FIG. 28 is an explanatory diagram of a process that selects pair rangecandidates;

FIG. 29 is an explanatory diagram of the pair range candidates selectedby the pair range candidate selection processing shown in FIG. 26;

FIG. 30 is flowchart of pair range determination processing that isperformed in the collation processing shown in FIG. 25;

FIG. 31 is a flowchart of calculation processing that is performed inthe pair range determination processing shown in FIG. 30;

FIG. 32 is a flowchart of frequency information similarity degreecalculation processing that is performed in the calculation processingshown in FIG. 31;

FIG. 33 is an explanatory diagram of a process that stores similaritydegree calculation pairs, similarity degrees, and angles;

FIG. 34 is a flowchart of pair range deletion processing that isperformed in the pair range determination processing shown in FIG. 30;

FIG. 35 is a graph showing authentication test results.

DETAILED DESCRIPTION OF EMBODIMENTS

An embodiment of the present disclosure will be explained with referenceto the drawings. Specific numerical values exemplified in the embodimentbelow are examples, and the present disclosure is not limited to thesenumerical values. In the explanation below, image data is simplyreferred to as an “image.”

A skin information processing device 10 that is common to first andsecond embodiments will be explained with reference to FIG. 1. The skininformation processing device 10 is an electronic device is configuredto generate, from skin information, collation information used forcollation. The skin information is selected from among various types ofbiometric information represented by an image obtained by capturinghairless skin, such as a finger, a palm, a sole of a foot and the like.The skin information of a present embodiment is information relating toa fingerprint and sweat pores. The skin information processing device 10is configured to analyze the image obtained by photographing a finger,generate collation information for collation that is necessary for thecollation using the skin information, and determine a correspondencebetween the generated collation information for collation and thecollation information for registration stored in the DB 28.

As shown in FIG. 1, the skin information processing device 10 isprovided with a CPU 1, a ROM 2, a RAM 3, the flash memory 4, acommunication I/F 5, a display portion 6, a touch panel 7 and a skininformation acquisition device 8. The CPU 1 is a processor that performscontrol of the skin information processing device 10. The CPU 1 iselectrically connected to the ROM 2, the RAM 3, the flash memory 4, thecommunication I/F 5, the display portion 6, the touch panel 7 and theskin information acquisition device 8. The ROM 2 stores a BIOS, a bootprogram and initial setting values. The RAM 3 stores various temporarydata. The flash memory 4 stores a program that is executed by the CPU 1to control the skin information processing device 10, an operatingsystem (OS) and the DB 28. The communication I/F 5 is a controller toperform communication with an external device. The display portion 6 isa liquid crystal display. The touch panel 7 is provided on the surfaceof the display portion 6. The skin information acquisition device 8acquires a captured image of skin. The skin information acquisitiondevice 8 of the present embodiment is an area-type optical sensor or amicroscope, and shows color information per pixel using 256 gray-scalevalues. The color information is information indicating color. In orderto acquire an image in which it is possible to ascertain the sweatpores, the resolution of the image is preferably 800 dots per inch (dpi)or greater. The resolution of the skin information processing device 10of the present embodiment is 2000 dpi, for example.

Ridge information storage processing that is performed in the skininformation processing device 10 of the first embodiment will beexplained with reference to FIG. 2 to FIG. 7, using a specific exampleshown in FIG. 4. As shown in FIG. 2, the skin information processingdevice 10 includes the skin information acquisition device 8, an imageacquisition portion 21, a base point determination portion 22, an sampleacquisition portion 23, a frequency information generation portion 24, aregistration portion 26, a collation portion 27 and the DB 28, andprocessing that corresponds to a functional block of each of them isperformed by the CPU 1 (refer to FIG. 1).

As shown in FIG. 3, the skin information acquisition device 8 outputs animage to the image acquisition portion 21. The image acquisition portion21 acquires the image output from the skin information acquisitiondevice 8 (step S1). In the specific example, the skin informationacquisition device 8 acquires an image 41. The resolution of the image41 is 2000 dpi, for example, and the image 41 is an image schematicallyshowing a part of a rectangular image of 480 pixels in the X direction(the left-right direction) and 800 pixels in the Y direction (theup-down direction). The base point determination portion 22 determines abase point representing a sweat pore on a ridge, from the image 41acquired at step S1, and acquires position information corresponding toa position of the base point on the image (step S2). For example, thebase point determination portion 22 determines an area centroid of anidentified sweat pore to be the base point representing the sweat pore.The position information of the base point is represented, for example,by two-dimensional coordinates of an image coordinate system. It isassumed that the two-dimensional coordinates of the image coordinatesystem of the present embodiment are coordinates that are set in unitsof pixels, on the basis of positions of pixels in the image. In theimage 41, the two-dimensional coordinates of the image coordinate systemare set as represented by X and Y. The CPU 1 causes the position of apixel on the top left of the image 41 to be an origin point of atwo-dimensional coordinate 46 of the image coordinate system. Theposition of a pixel that is separated from the origin point of thetwo-dimensional coordinate 46 by x pixels in the X positive direction,and by y pixels in the Y positive direction, is represented bycoordinates (x, y).

The base point determination portion 22 determines the base point usingthe following procedure, for example. As shown in FIG. 4, the base pointdetermination portion 22 generates, from the image 41 acquired at stepS1, an image 42 representing ridges, and an image 43 representingcircular graphics that include sweat pores. The image 42 can beacquired, for example, by performing binarization processing on theimage 41. In other examples, the image 42 can be obtained by applyingthe image 41 to a plurality of image processing filters that are used inprocessing of a minutia method. Within the image 42, black sectionsrepresent ridges, and white sections represent sections of troughsbetween the ridges. The image 43 can be obtained by applying the image41 to an image processing filter that can extract a section of aparticular range of gray values. The sweat pores are disposed on theridges. The base point determination portion 22 compares the image 42and the image 43 and identifies the circular sections disposed on theridges indicated by the black sections as the sweat pores. The basepoint determination portion 22 determines the area centroid of theidentified sweat pore to be the base point representing the sweat pore.In the processing at step S2, for example, a plurality of the basepoints are extracted, including base points P1 to P9 of an image 44.

The sample acquisition portion 23 acquires samples (step S3). The sampleis information that associates the color information corresponding to areference point with second position information corresponding to aposition of the reference point on the image. The reference points arepoints surrounding the base point determined at step S2. For example,the CPU 1 sets the reference points as points on the circumference of acircle whose center is the base point P, in accordance withpredetermined conditions. In accordance with the predeterminedconditions, taking a starting point T1 as a reference, the CPU 1 sets128 reference points Tm (m is an integer from 1 to 128) in order atequal intervals in the clockwise direction, on the circumference of acircle having a predetermined radius and centering on the selected basepoint P1. When the reference points Tm have coordinates in units ofsub-pixels, the color information is acquired using known bilinearinterpolation or bicubic interpolation. The CPU 1 acquires samples 95that associate color information Cm corresponding to the referencepoints Tm with the second position information. The samples 95 areassociated with first position information that indicates the positionof the base point P1 on the image. It is sufficient that the firstposition information is information that defines the position of thebase point P1 on the image. For example, the first position informationmay be absolute coordinates (for example, coordinates of the imagecoordinate system), relative coordinates, an acquisition order, or thelike. The first position information of the present example isrepresented by the coordinates of the image coordinate system. It issufficient that the second position information is information thatdefines the positions of the reference points Tm in relation to the basepoint P1. For example, the second position information may be absolutecoordinates (for example, coordinates of the image coordinate system),relative coordinates, an angle in relation to a reference, or the like.When the order of acquisition of the reference points is determined withrespect to a point used as the reference (the starting point, forexample), the second position information may be the order ofacquisition of the reference points. In the present example, the orderof acquisition of the reference points Tm is acquired as the secondposition information. The order of acquisition of the reference pointsT1 to T128 is 1 to 128, respectively. The plurality of samples 95 aresamples acquired for each of the plurality of reference points Tm whosepositions are different from each other. The CPU 1 uses, as sample data96, information that associates the plurality of samples 95 acquired forthe single starting point T1 with the first position information.

The frequency information generation portion 24 calculates frequencycomponents of changes in the color information with respect to thesecond position information for the plurality of samples 95 (the sampledata 96) acquired at step S116, and generates frequency information FJ(step S4). The frequency components are, for example, a known LPCspectrum, an LPC cepstrum, a group delay spectrum, and the like. Thefrequency components are, for example, the group delay spectrum (GDS),and are defined as the frequency derivative of a phase spectrum in apower transfer function. As shown in FIG. 5 and FIG. 6, a GDS 83calculated on the basis of the sample data 96 separates and emphasizesindividual peaks of the frequency spectrum of the sample data 96. Asshown in a list 83 in FIG. 7, the frequency information FJ is associatedwith a base point ID and the position information of the base point.

The registration portion 26 associates the frequency information FJgenerated at step S4 with the base points and stores the associatedinformation in the DB 28 as the collation information for registrationused in skin authentication (step S5). As shown in the list 84, theregistration portion 26 stores the base point ID, the positioninformation of the base point, and the frequency information FJ inassociation with each other. The collation portion 27 collates thecollation information for collation with the collation information forregistration stored in the DB 28, and performs the skin authentication.The skin information processing device 10 ends the processing.

1. Processing at Registration

The skin information processing performed by the skin informationprocessing device 10 according to the second embodiment will beexplained with reference to FIG. 8 to FIG. 34, taking a case ofregistering the collation information as an example. The skininformation processing is started when a user inputs a start command.The start command includes a command relating to whether the collationinformation acquired from the image is to be registered in the DB 28 asthe collation information for registration, or whether the similaritydegree of the collation information with the collation information forregistration registered in the DB 28 is to be calculated. When the CPU 1of the skin information processing device 10 detects the input of thestart command for the skin information processing, the CPU 1 reads out,to the RAM 3, a skin information processing program for performing theskin information processing stored in the flash memory 4, and performseach step of the processing (to be described below) in accordance withinstructions included in the skin information processing program. In apresent embodiment, feedback processing is performed that promptsre-input until biometric information is acquired that satisfies acondition (the sharpness of the image, for example) for extracting thefeature points. The skin information acquired by the skin informationprocessing satisfies a condition for extracting collation informationfrom the skin information using an algorithm. Information and dataacquired and generated in the course of the processing are stored in theRAM 3 as appropriate. Various setting values necessary to the processingare stored in advance in the flash memory 4. Hereinafter, step isabbreviated to “S”.

As shown in FIG. 8, the CPU 1 performs image analysis processing (S11).The image analysis processing will be explained with reference to FIG.9. When contact of a finger is detected, the skin informationacquisition device 8 outputs, to the CPU 1, a signal that can identifyan image in which the fingerprint and the sweat pores are captured. TheCPU 1 receives the output signal from the skin information acquisitiondevice 8. The CPU 1 acquires the image on the basis of the receivedsignal (S21). At S21, for example, the image 41 shown in FIG. 4 isacquired. Two-dimensional coordinates of an image coordinate systemexpressed by X and Y are set in the image 41. The CPU 1 performsbinarization processing on the image 41 acquired at S21, and acquiresthe image 42 representing the ridges (S22). The CPU 1 determines thebase points (S23). For example, the CPU 1 applies the image 41 to animage processing filter that can extract a section of a particular rangeof gray values and acquires the image 43, compares the image 42 with theimage 43, and identifies the circular sections disposed on the ridgesindicated by the black sections as the sweat pores. The CPU 1 determinesthe area centroid of the identified sweat pore to be the base pointrepresenting the sweat pore, and acquires position information of thedetermined base point. The position information of the presentembodiment is formed of pixel unit coordinates of the image coordinatesystem. The CPU 1 may take the size and shape etc. of the circularsection into account, as necessary, and determine whether or not todetermine the circular section to be the sweat pore. The CPU 1determines whether or not the numbers of base points determined at S23is larger than zero (S24). When the number of base points acquired atS23 is zero (no at S24), the CPU 1 ends the image analysis processingand returns the processing to the skin information processing shown inFIG. 8. When the number of base points acquired at S23 is greater thanzero (yes at S24), the CPU 1 performs connection information generationprocessing.

As shown in FIG. 10, in the connection information generationprocessing, the CPU 1 initializes a list (S31). The list stores theconnection information. When it is assumed that each of the plurality ofbase points determined in the processing at S23 is a target base pointPT, the connection information is information that associates positioninformation of the target base point PT with position information of aconnection base point PB. The connection base point PB is a base pointthat is disposed on the same continuous ridge as the target base pointPT, and that precedes or follows the target base point PT in thearrangement order on the same continuous ridge. The CPU 1 selects, asthe target base point PT, one of the plurality of base points determinedin the processing at S23 (S32). For example, the base point P1 in theimage 44 shown in FIG. 4 is selected as the target base point PT. TheCPU 1 selects a single candidate base point PK as a candidate for theconnection base point PB (S33). For example, the CPU 1 acquires, as thecandidate base points PK, the base points in order of closeness (basedon a Euclidean distance, for example) from the target base point PT,from among the plurality of base points determined in the processing atS23, for example. The CPU 1 selects the base point P4 as the candidatebase point PK, for example. The CPU 1 calculates a distance d betweenthe target base point PT selected in the processing at S32 and thecandidate base point PK selected in the processing at S33 (S34). Thedistance d is a Euclidean distance calculated on the basis of theposition information of the target base point PT and the positioninformation of the candidate base point PK, for example.

The CPU 1 determines whether the distance d calculated at S34 is smallerthan a threshold value (S35). The threshold value is set as appropriatewhile taking into account the distribution of the sweat pores on theskin. When the distance d is not smaller than the threshold value (no atS35), the CPU 1 performs processing at S40 to be described later. Whenthe distance d is smaller than the threshold value (yes at S35), the CPU1 refers to the image 42 and determines whether or not only black pixelsare present between the target base point PT and the candidate basepoint PK (S36). For example, white pixels are present between the targetbase point P1 and the candidate base point P4 (no at S36). In this case,the CPU 1 determines that the target base point PT and the candidatebase point PK are not disposed on the same continuous ridge. Thus, theCPU 1 determines whether, in the processing at S33, the base point otherthan the target base point PT has been selected as the candidate basepoint PK from among the plurality of base points determined in theprocessing at S23 (S40). When there is the base point that has not beenselected as the candidate base point PK in the processing at S33 (no atS40), the CPU 1 selects the next candidate base point PK (S33). Forexample, when P2 is selected as the candidate base point PK, thecalculated distance d is smaller than the threshold value (yes at S35),and the CPU 1 determines that only black pixels are present between thebase point P1 and the base point P2 (yes at S36). The CPU 1 determineswhether there is a space in the list for the target base point PT (S37).In the present embodiment, a predetermined number of the connection basepoints PB can be set for each one of the target base points PT, and anupper limit is set for the number of the connection base points PB thatcan be registered in the list. Taking into account the number ofbifurcations of the ridge, the predetermined number is 4, for example.

When there is no space in the list (no at S37), the CPU 1 determineswhether the distance d calculated at S34 is smaller than a value dmax(S38). dmax is a maximum value of the distance d stored in the list.When the distance d is not smaller than dmax (no at S38), the CPU 1performs the processing at S40. When the distance d is smaller than dmax(yes at S38), within the list for the target base points PT, thecandidate base point PK that is dmax is deleted, the candidate basepoint PK selected at S33 is added to the list in place of the deletedcandidate base point PK, and the list is updated (S39). In theprocessing at S37, when there is space in the list for the target basepoints PT (yes at S37), the CPU 1 adds the candidate base point PKselected at S33 to the list for the target base points PT (S39). When,among the plurality of base points determined in the processing at S23,there are the base points other than the target base point PT that havenot been selected as the candidate base point PK in the processing atS33 (no at S40), the CPU 1 returns the processing to S33. At S39 that isrepeatedly performed, as shown by a list 81 in FIG. 11, for the basepoint P1, the base points P2 and P3 are stored in the list. When all thebase points other than the target base point PT have been selected asthe candidate base point PK (yes at S40), the CPU 1 determines whetherall the base points have been selected as the target base point PT inthe processing at S32 (S41). When there is the base point that has notbeen selected as the target base point PT (no at S41), the CPU 1 returnsthe processing to S32. When all of the base points have been selected asthe target base point PT (yes at S41), the CPU 1 performs deletionprocessing (S49). In the deletion processing, processing is performed todelete from the list the base points that do not precede or follow thetarget base point PT in the arrangement order of the ridges.

As shown in FIG. 12, in the deletion processing, the CPU 1 selects thebase point, for which two or more candidate base points PK are stored,from among the plurality of base points, as the target base point PT(S42). For example, the CPU 1 selects the base point P1 as the targetbase point PT. The CPU 1 selects two base points from among the two ormore candidate base points PK for the target base point PT selected atS42 (S43). The CPU 1 selects the base points P2 and P3 as the two basepoints, for example. The CPU 1 calculates an angle AL, which is an angleformed between two line segments formed by connecting each of the twobase points selected at S43 and the target base point PT (S44). Forexample, the CPU 1 calculates the angle AL formed between a first linesegment connecting the base point P1 and the base point P2, and a secondline segment connecting the base point P1 and the base point P3. The CPU1 determines whether the angle AL calculated at S44 is smaller than athreshold value (S45). The threshold value at S45 is set while takinginto account a bending range of the ridge and an interval between thesweat pores.

In the specific example, it is determined that the angle AL formedbetween the first line segment and the second line segment is smallerthan the threshold value (yes at S45), and, of the two base points P2and P3 selected at S43, the base point P3 for which the distance fromthe base point P1 selected at S42 is farther is deleted from the list(S46). When the angle AL is not smaller than the threshold value (no atS45), or after the processing at S46, the CPU 1 determines whether allcombinations of the two or more candidate base points PK stored for thetarget base point P1 have been selected (S47). When there is acombination that has not been selected at S43 (no at S47), the CPU 1returns the processing to S43. For the base point P1, there are nocombinations that have not been selected at S43 (yes at S47). In thiscase, the CPU 1 determines whether all of the base points for which thetwo or more candidate base points PK are stored have been selected asthe target base point PT in the processing at S42 (S48). Of the basepoints for which the two or more candidate base points PK are stored,when there are the base points that have not been selected as the targetbase point PT in the processing at S42 (no at S48), the CPU 1 returnsthe processing to S42. When all of the base points for which the two ormore candidate base points PK are stored have been selected as thetarget base point PT in the processing at S42 (yes at S48), the CPU 1ends the deletion processing, and returns the processing to theconnection information generation processing shown in FIG. 10. As aresult of the deletion processing, some of the candidate base points PKstored in the list 81 shown in FIG. 11 are deleted and updated to a list84.

As shown in FIG. 10, the CPU 1 performs list correction processing afterthe processing at S49 (S50). The list correction processing isprocessing to correct the list such that the target base point PT isstored as the candidate base point PK, when the candidate base point PKstored for the target base point PT is taken as the target base pointPT. As shown in FIG. 13, in the list correction processing, the CPU 1selects, from among the plurality of base points, one of the base pointsas the target base point PT (S51). For example, the CPU 1 selects thebase point P1 as the target base point PT. The CPU 1 determines whetherthe number of the candidate base points PK stored for the target basepoint PT selected at S51 is greater than zero (S52). When the number ofthe candidate base points PK is not greater than zero (no at S52), theCPU 1 performs processing at S58 to be described later. The onecandidate base point PK is stored for the target base point P1 (yes atS52), and thus the CPU 1 selects the one candidate base point PK for thetarget base point PT selected at S51, from the list (S53). The CPU 1selects the base point P2 as the candidate base point PK for the basepoint P1. The CPU 1 determines whether the base point P1 selected at S51is stored in the list as the candidate base point PK for the base pointP2 selected at S53 (S54). When the base point selected at S51 is notstored as the candidate base point PK for the base point selected at S53(no at S54), if there is a space in the list of the base points selectedat S53 (yes at S55), the CPU 1 stores the base point selected at S51 asthe candidate base point PK for the base point selected at S53 (S56).When there is no space in the list of the base points selected at S53(no at S55), or after the processing at S56, the CPU 1 performsprocessing at S57.

The base point P1 is stored in the list as the candidate base point PKfor the base point P2 (yes at S54). In this case, the CPU 1 determineswhether all of the candidate base points PK for the target base point PTselected at S51 have been selected in the processing at S53 (S57). Ofthe candidate base points PK for the target base point PT, when there isthe base point that has not been selected in the processing at S53 (noat S57), the CPU 1 returns the processing to S53. When all the candidatebase points PK for the target base point PT have been selected in theprocessing at S53 (yes at S57), the CPU 1 determines whether all of theplurality of base points have been selected as the target base point PTin the processing at S51 (S58). When there is the base point that hasnot been selected as the target base point PT (no at S58), the CPU 1returns the processing to S51. When all the base points have beenselected as the target base point PT (yes at S58), the CPU 1 ends thelist correction processing and returns the processing to the connectioninformation generation processing shown in FIG. 10. After ending thelist correction processing at S50, the CPU 1 ends the connectioninformation generation processing and returns the processing to theimage analysis processing shown in FIG. 9. The candidate base point PKresulting from the connection information generation processing isidentified as the connection base point PB for the target base point PT,and the position information of the target base point PT and theposition information of the connection base point PB are associated witheach other and stored as connection information 85. As shown in FIG. 11,in the connection information 85, for example, the position informationof the base point P1 and the position information of the base point P2are associated with each other as connection information B1 for the basepoint P1. The position information of the base point P2, and theposition information of the base points P1 and P3 are associated witheach other as connection information B2 for the base point P2.

As shown in FIG. 9, after the processing at S25, the CPU 1 performsridge information generation processing (S26). As shown in FIG. 14, inthe ridge information generation processing, the CPU 1 selects one ofthe base points from among the plurality of base points as the targetbase point PT (S61). For example, the CPU 1 selects the base point P1shown in FIG. 15 as the target base point PT. The CPU 1 refers to theconnection information 85 generated in the processing at S25, anddetermines whether the number of the connection base points PB storedfor the target base point PT selected in the processing at S61 is 1(S62). By the processing at S62, on the basis of the connectioninformation, the CPU 1 identifies, among the plurality of base points,the base point for which a number of preceding and following base pointsin the arrangement order is 1, and identifies the first base point inthe arrangement order as a start point and the last base point in thearrangement order as an end point. When the number of the connectionbase points PB is not 1 (no at S62), the CPU 1 performs processing atS75 to be described later. For the base point P1, the number of theconnection base points PB is 1 (yes at S62). In this case, the CPU 1refers to the already stored ridge information and determines whetherthe target base point PT selected in the processing at S61 is not storedas the base point of the other ridge information (S63). When the targetbase point PT selected in the processing at S61 is stored as the basepoint of the other ridge information, for example, for the base pointfor which the number of preceding and following base points in thearrangement order is 1, the target base point PT is identified as thelast base point in the arrangement order in the other ridge information.When the target base point PT is stored as the base point of the otherridge information (yes at S63), the CPU 1 performs the processing at S75to be described later. The base point P1 is not stored as the base pointof the other ridge information (no at S63). In this case, the CPU 1performs initialization processing relating to ridge information Ri(S64). In the initialization processing relating to the ridgeinformation Ri, the CPU 1 initializes the i-th ridge information Ri, abranch point list, and an already selected list, and sets values toNULL. i is a natural number indicating a registration order of the ridgeinformation. The initial value of i is 1, and is incremented inaccordance with the number of the already registered ridge information.The CPU 1 adds the target base point PT to the ridge information Ri(S65). For example, as in a list 86 shown in FIG. 16, the CPU 1 adds thebase point ID and the position information (X1, Y1) of the base point P1to ridge information R1. By repeating the processing at S65, on thebasis of the connection information generated in the processing at S25,the plurality of base points disposed on the same continuous ridge areextracted in order. The CPU 1 adds the base point P1 to the alreadyselected list, and updates the already selected list (S66). The CPU 1sets a various N to 1, the variable N indicating the number of the basepoints included in the ridge information Ri (S67).

The CPU 1 refers to the connection information 85 generated in theprocessing at S25, and selects, as a selected base point, the connectionbase point PB stored for the target base point PT selected in theprocessing at S61 (S68). For example, the CPU 1 selects the base pointP2 as the selected base point. The CPU 1 performs angle calculationprocessing (S69). As shown in FIG. 17, in the angle calculationprocessing, the CPU 1 determines whether the selected base point hasalready been stored as the base point of the other ridge information(S81). When the selected base point has been stored as the base point ofthe other ridge information (yes at S81), the CPU 1 ends the anglecalculation processing and returns the processing to the ridgeinformation generation processing shown in FIG. 14. As shown by the list86 in FIG. 16, the base point P2 is not stored as the base point in theother ridge information (no at S81). In this case, the CPU 1 calculatesa relative angle for the selected base point (S82). The relative angleis an angle of the second line segment connecting the N-th base point inthe arrangement order and the (N+1)-th selected base point in thearrangement order with respect to the first line segment connecting the(N−1)-th base point in the arrangement order and the N-th base point inthe arrangement order. In other words, the relative angle is the angleof the line segment connecting the N-th base point and the followingbase point in the arrangement order with respect to the line segmentconnecting the N-th base point and the preceding base point in thearrangement order. When N is 1, the CPU 1 sets the relative angle aszero. When N is 2 or more, the CPU 1 defines the first line segment andthe second line segment and calculates the relative angle. In thepresent embodiment, an angle in the clockwise direction from the firstline segment is taken as a positive angle, and an angle in thecounterclockwise direction from the first line segment is taken as anegative angle, and the relative angle is represented by an angle from−180 degrees to 180 degrees. In the specific example, N is 1, and thusthe CPU 1 sets the relative angle for the base point P1 as zero.

The CPU 1 determines whether the relative angle calculated at S82 issmaller than a threshold value (S83). When the relative angle is notsmaller than the threshold value (no at S83), the CPU 1 ends the anglecalculation processing and returns the processing to the ridgeinformation generation processing shown in FIG. 14. When the relativeangle is smaller than the threshold value (yes at S83), the CPU 1 addsthe selected base point to the ridge information Ri (S84). The CPU 1adds the base point ID and the position information of the selected basepoint, a relative angle AN calculated at S82, and the distance d betweenthe target base point PT included in the connection information and theselected base point to the ridge information Ri. The CPU 1 adds the basepoint P2 to the ridge information R1, as shown in a list 87 in FIG. 16.The CPU 1 adds the selected base point to the already selected list andupdates the already selected list. The CPU 1 increments N by 1 (S85).

The CPU 1 refers to the connection information 85 generated in theprocessing at S25 and determines whether the number of the connectionbase points PB stored for the selected base point is greater than 1(S86). The selected base point for which the number of the connectionbase points PB is 1 is the other end of the ridge. When the number ofthe connection base points PB is not greater than 1 (no at S86), the CPU1 ends the angle calculation processing and returns the processing tothe ridge information generation processing shown in FIG. 14. When thenumber of the connection base points PB is greater than 1 (yes at S86),the CPU 1 determines whether the number of the connection base points PBis greater than 2 (S87). The processing at S87 is processing toidentify, among the plurality of base points, the base point for whichthe number of preceding and following base points in the arrangementorder is 3 or more, as the branch point of the ridge, on the basis ofthe connection information. Processing that is performed when the numberof the connection base points PB is greater than 2 (yes at S87) will bedescribed later. The number of the connection base points PB for thebase point P2 is 2 (no at S87). In this case, the CPU 1 sets theselected base point as the target base point PT and returns theprocessing to S68 in FIG. 14. At S68 that is repeatedly performed, whenthe target base point PT is the base point P2, the CPU 1 selects thebase point P3 as the connection base point (S68). In the anglecalculation processing shown in FIG. 17, it is determined that the basepoint P3 has not yet been selected (yes at S81), and a relative angleAN2 is calculated (S82). It is determined that the relative angle AN2 issmaller than the threshold value (yes at S83), and the CPU 1 adds thebase point P3 to the ridge information R1, as shown in a list 88 in FIG.16 (S84). The CPU 1 adds the base point P3 to the already selected listand updates the already selected list. The CPU 1 increments N by 1(S85). Since the number of the connection base points PB for the basepoint P3 is 1 (no at S86), the CPU 1 ends the angle calculationprocessing and returns the processing to the ridge informationgeneration processing shown in FIG. 14. In this way, when the continuousridge does not include the branch point, the CPU 1 defines the ridgehaving no bifurcations from the start point to the end point, extractsthe plurality of base points disposed on the defined ridge, andgenerates the ridge information.

In the ridge information generation processing shown in FIG. 14, the CPU1 determines whether or not the variable N is larger than a thresholdvalue (S70). The processing at S70 is processing to generate only theridge information including the number of base points greater than thethreshold value. The threshold value is 2, for example. If the variableN is not larger than the threshold value (no at S70), the CPU 1 deletesthe ridge information Ri without registering it (S71). For the ridgeinformation R1, the variable N is 3 and is larger than the thresholdvalue (yes at S70). In this case, the CPU 1 generates the ridgeinformation R1 (S72). After step S72 or step S71, the CPU 1 determineswhether the base point is included in the branch point list (S73). Whenthe base point is included in the branch point list (yes at S73), theCPU 1 performs branch point processing (S74). When the base point is notincluded in the branch point list (no at S73), the CPU 1 performs theprocessing at S75 to be described later.

At S87, when a base point P13 shown in FIG. 15 is selected as a selectedbase point for ridge information R3, as shown in connection informationB13 in FIG. 11, the number of the connection base points PB for the basepoint P13 is 3 and is thus greater than 2 (yes at S87). In this case,the CPU 1 adds the selected base point and the ridge information Ri tothe branch point list (S88). As shown in FIG. 18, the CPU 1 stores thebase point P13, and L3 that is the ridge ID of the ridge information R3in a branch point list 91. The CPU 1 takes the selected base point asthe target base point PT, and, from among the connection base points PBfor the target base point PT, selects the base point that is not in thealready selected list as the selected base point (S89). As shown in FIG.18, from among the connection base points PB for the target base pointPT, the CPU 1 stores the base point that has not already been selectedas the selected base point in association with the ridge information Riof the branch point list (S90). The CPU 1 refers to the connectioninformation 85 shown in FIG. 11, and, from among the connection basepoints PB for the base point P13, adds the base point P17 that is notstored in the already selected list to the branch point list 91, inassociation with the base point P13. The CPU 1 returns the processing toS81. At S81, the CPU 1 determines whether the selected base pointselected at S89 is stored as the base point of the other ridgeinformation (S81).

At S73 in relation to the ridge information R3, it is determined thatthe base point P13 is stored in the branch point list 91 shown in FIG.18 (yes at S73). In this case, the CPU 1 performs the branch pointprocessing (S74). As shown in FIG. 19, in the branch point processing,the CPU 1 selects the branch base point stored in the branch point listas the target base point PT, and selects the connection base point thatis linked and stored with the branch base point as the selected basepoint (S101). The CPU 1 selects the base point P13 stored in the branchpoint list 91 as the target base point PT, and selects the base pointP17 as the selected base point. The CPU 1 increments i by 1, and setsthe new ridge information Ri (S102). The CPU 1 generates new ridgeinformation R4. More specifically, the CPU 1 copies the ridgeinformation from the start point of ridge information R (i−1) to thetarget base point PT into the ridge information Ri (S102). The CPU 1copies the ridge information R3 from the base point P11 to the basepoint P13 into the ridge information R4. The CPU 1 sets the number ofbase points included in the ridge information Ri as the variable N(S103). The CPU 1 sets the variable N to 3 for the ridge information R4.The CPU 1 deletes the base point P13 that is the target base point PTfrom the branch point list (S104). The CPU 1 ends the branch pointprocessing and returns the processing to the ridge informationgeneration processing shown in FIG. 14. After the processing at S74, theCPU 1 returns the processing to S69. As described above, when the branchpoint is included in the continuous ridge, the CPU 1 defines theplurality of ridges having no bifurcations from the start point to theend point, including that branch point, such that the number of thebifurcating ridges corresponds to the number of bifurcations at thebranch points. Then, the CPU 1 extracts the plurality of base pointsdisposed on the same ridge for each of the defined plurality of ridges,and generates the ridge information.

At S75 shown in FIG. 14, the CPU 1 determines whether all of the basepoints have been selected as the target base point PT in the processingat S61 (S75). When at least one of the base points has not been selectedas the target base point PT (no at S75), the CPU 1 returns theprocessing to S61. When all of the base points have been selected as thetarget base point PT (yes at S75), the CPU 1 ends the ridge informationgeneration processing and returns the processing to the image analysisprocessing shown in FIG. 9. By the ridge information generationprocessing shown in FIG. 14, as shown in a list 89 in FIG. 16, thepieces of the ridge information R1 to ridge information R6 are generatedcorresponding to each of the ridges L1 to L6.

The CPU 1 performs frequency information generation processing after theprocessing at S26 (S27). As shown in FIG. 20, in the frequencyinformation generation processing, the CPU 1 selects one of the piecesof ridge information from among the plurality of pieces of ridgeinformation generated by the processing at S26 (S111). For example, theCPU 1 selects the ridge information R1 from the list 89 shown in FIG.16. From among the base points P1 to P3 included in the ridgeinformation R1 selected at S111, the CPU 1 selects, as a start point,the base point P1 that is first in the arrangement order (S112). The CPU1 determines whether or not the position information of the selectedbase point P1 is inside an effective range of the image acquired at S21(S113). The effective range is a region in which the samples can beacquired and a region in which the biometric information can beacquired. There is a case in which the image representing the skininformation is not acquired over the whole of an image capturable rangeof the skin information acquisition device 8, and, in the imagecapturable range, there is a region that is not touched by the finger ofthe user, for example. The skin information does not appear in the imageof this type of region. For example, since the skin information does notappear in a white image region corresponding to the region that is nottouched by the user's finger, the CPU 1 of the present embodiment doesnot extract the samples of points that are not in the effective range.Thus, for example, when a peak value of a power spectrum of atwo-dimensional Fourier transform of color information of a specifiedrange centering on the selected base point is equal to or greater than aconstant value, the CPU 1 determines that the position information ofthe selected base point is in the effective range. In another example,when the sum of absolute values of values obtained by applying adifferential filter to the color information of a predetermined rangeincluding the selected base point, or the sum of squares is equal to orgreater than a constant value, the CPU 1 determines that the positioninformation of the selected base point is in the effective range.

When the position information of the selected base point is not in theeffective range (no at S113), the CPU 1 performs processing at S123 tobe described later. When the position information of the selected basepoint is in the effective range (yes at S113), the CPU 1 refers to theridge information R1 selected at S111, and determines whether, in thearrangement order, there is the base point after the selected base pointP1 (S114). When there is no base point after the selected base point (noat S114), the CPU 1 performs processing at S118 to be described later.In the ridge information R1, the base point P2 is included that is afterthe base point P1 in the arrangement order (yes at S114). In this case,the CPU 1 calculates a direction U1 of a vector from the selected basepoint P1 toward the base point P2 that is next in the arrangement order(S115). The CPU 1 acquires the color information indicating the coloraround the selected base point P1, on the basis of the direction U1calculated at S115 (S116).

More specifically, the CPU 1 determines a point for which a distancefrom the selected base point P1 is a predetermined value, and which isin the direction U1 calculated at S115 with respect to the base pointP1, as a starting point T1. The CPU 1 acquires a predetermined number ofreference points in accordance with predetermined conditions. As shownin FIG. 21, for example, in accordance with the predeterminedconditions, taking the starting point T1 as a reference, the CPU 1 sets128 reference points Tm (m is an integer from 1 to 128) in order atequal intervals in the clockwise direction, on the circumference of acircle having a predetermined radius and centering on the selected basepoint P1. When the reference points Tm have coordinates in units ofsub-pixels, the color information is acquired using known bilinearinterpolation or bicubic interpolation. The CPU 1 acquires samples 95that associate color information Cm corresponding to the referencepoints Tm with second position information. The samples 95 areassociated with the first position information that indicates theposition of the base point P1 on the image. It is sufficient that thefirst position information is information that defines the position ofthe base point P1 on the image. For example, the first positioninformation may be absolute coordinates (for example, coordinates of theimage coordinate system), relative coordinates, an acquisition order, orthe like. The first position information of the present embodiment isrepresented by the coordinates of the image coordinate system. It issufficient that the second position information is information thatdefines the positions of the reference points Tm in relation to the basepoint P1. For example, the second position information may be absolutecoordinates (for example, coordinates of the image coordinate system),relative coordinates, an angle in relation to a reference, or the like.When the order of acquisition of the reference points is determined withrespect to a point used as the reference (the starting point, forexample), the second position information may be the order ofacquisition of the reference points. In the present embodiment, theorder of acquisition of the reference points Tm is acquired as thesecond position information. The order of acquisition of the referencepoints T1 to T128 is 1 to 128, respectively. The plurality of samples 95are samples acquired for each of the plurality of reference points Tmwhose positions are different from each other. The CPU 1 uses, as sampledata 96, information that associates the plurality of samples 95acquired for the single starting point T1 with the first positioninformation.

The CPU 1 calculates frequency components of changes in the colorinformation with respect to the second position information for theplurality of samples 95 (the sample data 96) acquired at S116, andgenerates frequency information (S117). The frequency components are,for example, a known LPC spectrum, an LPC cepstrum, a group delayspectrum, and the like. The frequency components are, for example, thegroup delay spectrum (GDS), and are defined as the frequency derivativeof a phase spectrum in a power transfer function. The CPU 1 uses alinear prediction coefficient, which is calculated using the Yule-Walkermethod without multiplying a window function, to calculate the frequencyinformation. Specifically, the CPU 1 uses the linear predictioncoefficient calculated using the Yule-Walker method without multiplyingthe window function, and calculates the GDS by obtaining the phasederivative of a power spectrum obtained by performing a high-speedFourier transform on a weighted LPC coefficient. The CPU 1 uses thecalculated GDS as the frequency information.

The CPU 1 refers to the ridge information R1 selected at S111, anddetermines whether there is the base point that is before the selectedbase point P1 in the arrangement order (S118). There is no base pointthat is before the selected base point P1 in the arrangement order (noat S118). In this case, the CPU 1 performs processing at S122 to bedescribed later. When there is the base point that is before the basepoint in the arrangement order (yes at S118), the CPU 1 calculates adirection U of a vector from a selected base point Pk toward the basepoint that is before the base point Pk in the arrangement order (S119).When the selected base point Pk is the base point P2 (yes at S118),using a similar procedure to the processing at S116, the CPU 1 acquiresthe color information indicating the color around the selected basepoint P2, on the basis of a direction U2 from the base point P2 towardthe base point P1 (S120). Using a similar procedure to the processing atS117, the CPU 1 calculates the frequency components of the changes inthe color information with respect to the second position informationfor the plurality of samples 95 (the sample data 96) acquired at S120(S121). The CPU 1 stores the frequency information generated at at leastone of S117 and S121 in association with the selected base point (S122).The CPU 1 determines whether the base points included in the ridgeinformation selected at S111 have been selected by the processing atS112 or by processing at S124 (S123). When there is the base point thathas not been selected (no at S123), the CPU 1 selects the next basepoint in the arrangement order (S124), and returns the processing toS113.

When all of the base points included in the ridge information selectedat S111 have been selected (yes at S123), the CPU 1 determines whetherall of the ridge information generated by the processing at S26 has beenselected at S111 (S125). When there is the unselected ridge information(no at S125), the CPU 1 returns the processing to S111. When all of theridge information has been selected by the processing at S111 (yes atS125), the CPU 1 ends the frequency information generation processingand returns the processing to the image analysis processing shown inFIG. 9. In the image analysis processing shown in FIG. 9, after S27, theCPU 1 associates the ridge information generated at S26 with thefrequency information generated at S27, as shown in a list 98 in FIG.22, and stores the associated information as the collation informationused in the authentication of the skin information (S28). The CPU 1 endsthe image analysis processing and returns the processing to the skininformation processing shown in FIG. 8. After the processing at S11, theCPU 1 determines whether the collation information including the ridgeinformation has been acquired at S11 (S12). When the collationinformation has not been acquired (no at S12), the CPU 1 performs errornotification (S16). For example, the CPU 1 displays an error message onthe display portion 6. When the collation information has been acquired(yes at S12), it is determined whether to register the collationinformation acquired at S11 in the DB 28 (refer to FIG. 2) as thecollation information for registration (S13). The information indicatingwhether to perform the registration is included in the start command,for example. In the specific example, it is determined that theregistration is to be performed (yes at S13), and the CPU 1 stores thecollation information acquired at S11 in the DB 28 of the flash memory 4(S14). When the collation information is not to be registered in the DB28 (no at S13), the CPU 1 performs collation processing to set thecollation information acquired at S11 that is a collation target as thecollation information for collation (S15). After one of S14, S15, orS16, the CPU 1 ends the skin information processing.

2. Processing at Collation

The skin information processing at the time of collation will beexplained taking a case as an example in which the pieces of ridgeinformation R1 to R6 extracted from the image 41 shown in FIG. 15 isused as the collation information for registration, and an image 61shown in FIG. 23 is acquired as a collation image that is the collationtarget. In the skin information processing at the time of collation, S11is performed similarly to the skin information processing at the time ofregistration. For example, base points Q1 to Q27 shown in FIG. 23 aredetermined as the base points at S23 shown in FIG. 9. On the basis ofthe base points Q1 to Q27 shown in FIG. 23, the pieces of ridgeinformation V1 to V5 shown in a list 92 in FIG. 24 are generated forridges Z1 to Z5. In the following explanation, the ridge information forcollation is denoted by ridge information Vn (where n is an integer),and the ridge information for registration is denoted by ridgeinformation Rm (where m is an integer) and the two are thusdistinguished from each other. The base point for collation is denotedby a base point Qj (where j is an integer) and the base point forregistration is denoted by a base point Pk (where k is an integer), andthe two are thus distinguished from each other.

At S12 shown in FIG. 8, it is determined that the collation informationhas been acquired (yes at S12), and it is determined on the basis of thestart command that registration is not to be performed (no at S13). TheCPU 1 performs the collation processing (S15). In the collationprocessing, the CPU 1 determines a correspondence between the ridgeinformation Rm and the ridge information Vn. The CPU 1 calculates asimilarity degree W for the determined correspondence, and performs theskin authentication.

In the collation processing, as shown in FIG. 25, the CPU 1 performspair range candidate selection processing (S201). The pair rangecandidate selection processing is processing to select candidates for apair range. The pair range is a range over which, among a plurality ofcombinations of the collation ridge information Vn and the registrationridge information Rm, a difference between the selected collation ridgeinformation and the selected registration ridge information is equal toor lower than a threshold value for equal to or greater than apredetermined number of the continuous base points. In the pair rangecandidate selection processing, the CPU 1 selects candidates for apositional correspondence, which is a correspondence between the basepoint of the collation ridge information used in the skinauthentication, and the base point of the registration ridge informationstored in the storage portion. In the pair range candidate selectionprocessing, as shown in FIG. 26, with respect to all of the ridgeinformation V1 to V5 generated on the basis of the collation image 61,the CPU 1 generates pieces of ridge information v1 to v5 in which thestart points and the end points have been inverted (S211). For each ofall the pieces of ridge information V1 to V5 generated on the basis ofthe collation image 61 and shown in the list 92 in FIG. 24, the CPU 1inverts the arrangement order of the base points and generates thepieces of ridge information v1 to v5. In the pieces of ridge informationv1 to v5, for the position information and the distances, the valuescorresponding to the base points are used as they are. The relativeangle is a value obtained by multiplying a relative angle AN by −1.

The CPU 1 selects one of the pieces of ridge information from theplurality of pieces of ridge information that include the pieces ofridge information V1 to V5 generated on the basis of the collation image61 and the pieces of ridge information v1 to v5 generated at S211(S212). For example, the CPU 1 selects the ridge information V1 for theridge Z1. The CPU 1 selects one of the pieces of ridge information fromthe pieces of ridge information R1 to R6 generated on the basis of theregistration image 41 (S213). The CPU 1 selects the ridge information R1for the ridge L1.

The CPU 1 sets the variable N to 1, and sets the similarity degree W tozero (S214). The variable N indicates a number of pairs of the basepoints included in the pair range candidates. Among the combinations ofthe base point Pk included in the ridge information Rm and the basepoint Qj included in the ridge information Vn, the pair refers to acombination for which a similarity degree w calculated at S217 (to bedescribed later) is equal to or lower than a threshold value. The CPU 1selects the one base point that is next in the arrangement order fromamong the base points Qj included in the ridge information Vn (S215).For example, the CPU 1 selects the base point Q1 that is first in thearrangement order of the ridge information V1 shown in FIG. 24. The CPU1 selects the one base point that is next in the arrangement order fromamong the base points Pk included in the ridge information Rm (S216).For example, the CPU 1 selects the base point P1 that is first in thearrangement order of the ridge information R1 shown in FIG. 16.

The CPU 1 compares the base point Qj selected at S215 and the base pointPk selected at S216 and calculates the similarity degree w (S217). TheCPU 1 compares the relative angles and the distances of the base pointQj and the base point Pk, applies a comparison result to a predeterminedarray, and calculates the similarity degree w. Compared to when thesimilarity degree w is smaller, the larger the similarity degree w, thegreater it is estimated that the base point Qj and the base point Pk aresimilar points. When at least one of the base point Qj selected at S215and the base point Pk selected at S216 is the start point (the firstpoint in the arrangement order) or the end point (the last point in thearrangement order) of a line segment group that is represented by thecorresponding ridge information, the CPU 1 sets a constant as thesimilarity degree w. The constant is larger than the threshold value atS218 to be described later. Both the base point Q1 and the base point P1are the start point of the line segment group represented by the ridgeinformation, and the constant is set as the similarity degree w.

The CPU 1 determines whether the similarity degree w calculated at S217is larger than the threshold value (S218). The similarity degree w ofthe specific example is larger than the threshold value (yes at S218).In this case, the CPU 1 increments the variable N by 1, adds thesimilarity degree w calculated in the processing at S217 to thesimilarity degree W, and updates the similarity degree W (S221). Asshown in a list 71 in FIG. 28, the CPU 1 adds the base point Q1 selectedat S215 and the base point P1 selected at S216 to the pair rangecandidates relating to the ridge information V1 selected at S212 and theridge information R1 selected at S213 (S222). The CPU 1 determineswhether the base point Q1 selected at S215 is the end point of the ridgeinformation V1 selected at S212 (S223). When the base point Qj selectedat S215 is the end point of the ridge information Vn selected at S212(yes at S223), the CPU 1 performs processing at S231 to be describedlater. The base point Q1 is not the end point of the ridge informationV1 (no at S223). In this case, the CPU 1 determines whether the basepoint P1 selected at S216 is the end point of the ridge information R1selected at S213 (S224). When the base point Pk selected at S216 is theend point of the ridge information Rm selected at S213 (yes at S224),the CPU 1 performs the processing at S231 to be described later. Thebase point P1 is not the end point of the ridge information R1 (no atS224). In this case, the CPU 1 selects the one base point that is nextin the arrangement order, for each of the ridge information V1 selectedat S212 and the ridge information R1 selected at S213 (S225). The CPU 1selects the base point Q2 as the base point that is next in thearrangement order of the ridge information V1, after the base point Q1.The CPU 1 selects the base point P2 as the base point that is next inthe arrangement order of the ridge information R1, after the base pointP1.

The CPU 1 returns the processing to S217, and calculates the similaritydegree w between the base point Q2 and the base point P2 (S217). It isdetermined that the similarity degree w between the base point Q2 andthe base point P2 is not larger than the threshold value (no at S218),and the CPU 1 determines whether N is larger than a threshold value ornot (S231). The processing at S231 is processing to extract, as the pairrange candidates, the pairs of the line segment group for which thenumber of pairs is larger than a threshold value. The threshold value is3, for example. In the specific example, N is 2 (no at S231), and, ofthe pairs relating to the ridge information V1 stored at S222 andselected at S212 and the ridge information R1 selected at S213, the CPU1 deletes a pair for which the start point is the base point Q1 selectedat S215 and the base point P1 selected at S216, from the pair rangecandidates (S232).

When the variable N is larger than the threshold value (yes at S231), orafter S232, the CPU 1 determines whether all of the base points of theridge information R1 selected at S213 have been selected by theprocessing at S216 (S233). When the base point Pk selected at S216 isthe last base point in the arrangement order of the plurality of basepoints included in the ridge information R1 selected at S213, the CPU 1determines that all the base points of the ridge information R1 selectedat S213 have been selected by the processing at S216 (yes at S233). Thebase point P1 selected by the processing at S216 is not the last basepoint in the ridge information R1 (no at S233). In this case, the CPU 1selects the base point P2 that is the next base point after the basepoint P1 in the arrangement order, from the ridge information R1selected by the processing at S213. When all of the base points of theridge information R1 selected at S213 have been selected by theprocessing at S216 (yes at S233), the CPU 1 determines whether all thebase points of the ridge information V1 selected at S212 have beenselected by the processing at S215 (S234). When the base point Qjselected at S215 is the last base point in the arrangement order of theplurality of base points included in the ridge information V1 selectedat S212, the CPU 1 determines that all of the base points of the ridgeinformation V1 selected at S212 have been selected by the processing atS215 (yes at S234). When the base point Q selected by the processing atS215 is the base point Q1, this is not the last base point in thecollation ridge information selected at S212 (no at S234).

In this case, the CPU 1 returns the processing to S215, and, of theridge information Vn selected at S212, selects the next base point inthe arrangement order after the base point Qj selected in the previousprocessing at S215 (S215). At S216 after the processing at S215, of theregistration ridge information selected at S213, the first base point inthe arrangement order is selected. When all the base points of the ridgeinformation Vn selected at S212 have been selected by the processing atS215 (yes at S234), of the pair range candidates relating to the ridgeinformation Vn selected at S212 and the ridge information Rm selected atS213, the CPU 1 leaves only the pair range candidates for which thesimilarity degree W added up at S221 is the largest, and deletes theother pair range candidates (S235). The CPU 1 determines whether or not,in relation to the ridge information Vn selected at S212, all of thepieces of ridge information Rm have been selected by the processing atS213 (S236). When, in relation to the ridge information Vn selected atS212, the ridge information Rm is remaining that has not been selectedat S213 (no at S236), the CPU 1 returns the processing to S213, andselects the ridge information Rm that has not yet been selected (S213).When the ridge information V1 is selected at S212, the ridge informationR2 is selected at S213, the base point Q1 is selected at S215, and thebase point P4 is selected at S215, by the processing at S222 that isrepeatedly performed, six pairs of the base points are stored in a list72 shown in FIG. 28, as the pair range candidates. At S223, the basepoint Q6 is determined to be the end point (yes at S223), and thevariable N is 7, and is determined to be larger than the threshold value(yes at S231). By the same processing, when the ridge information V1 isselected at S212, the ridge information R2 is selected at S213, the basepoint Q2 is selected at S215, and the base point P5 is selected at S215,by the processing at S222 that is repeatedly performed, five pairs ofthe base points are stored in a list 73 shown in FIG. 28, as the pairrange candidates. When the ridge information V1 is selected at S212 andthe ridge information R2 is selected at S213, at S235, as the pair rangecandidate relating to the ridge information V1 and the ridge informationR2, only the base points of the six pairs shown in the list 72 for whichthe similarity degree W is largest are left and the other pair rangecandidates are deleted.

When all the pieces of ridge information Rm in relation to the ridgeinformation Vn selected at S212 have been selected at S213 (yes atS236), the CPU 1 determines whether or not all the pieces of ridgeinformation Vn have been selected in the processing at S212 (S238). Whenthere is the ridge information Vn that has not been selected at S212 (noat S238), the CPU 1 returns the processing to S212, and selects theridge information Vn that has not yet been selected (S212). When all thepieces of ridge information Vn have been selected at S212 (yes at S238),the CPU 1 ends the pair range candidate selection processing and returnsthe processing to the collation processing shown in FIG. 25. As a resultof the pair range candidate selection processing shown in FIG. 26, thepair range candidates shown in FIG. 29 are selected. As shown in FIG.29, with respect to the ridge information V1 for the ridge Z1, and theridge information R2 for the ridge L2, the six pairs of the base pointsare stored as the pair range candidates. With respect to the ridgeinformation V2 for the ridge Z2, and the ridge information R3 for theridge L3, the six pairs of the base points are stored as the pair rangecandidates. With respect to the ridge information V3 for the ridge Z3,and the ridge information R4 for the ridge L4, the six pairs of the basepoints are stored as the pair range candidates. With respect to theridge information V4 for the ridge Z4, and the ridge information R5 forthe ridge L5, the five pairs of base points are stored as the pair rangecandidates. With respect to the ridge information V5 for the ridge Z5,and the ridge information R6 for the ridge L6, the four pairs of basepoints are stored as the pair range candidates. With respect to theridge information V5 and the ridge information R5 for the ridge L5, thefour pairs of base points are stored as the pair range candidates. Thereis a case in which, as with the ridge information V5, a specified rangeof the one piece of ridge information Vn and a specified range of aplurality of the pieces of ridge information Rm are used as thecandidates for the pair range. By the processing at S201, the determinedplurality of sets of registration line segment information and collationline segment information are acquired as the combinations used in thecalculation of the similarity degree.

After the processing at S201 shown in FIG. 25, the CPU 1 performs pairrange determination processing (S202). In the pair range determinationprocessing, the CPU 1 determines the pair range on the basis of the pairrange candidates selected at S201, and calculates a similarity degree WRbetween the collation ridge information and the registration ridgeinformation, on the basis of the determined positional correspondence.As shown in FIG. 30, in the pair range determination processing, the CPU1 determines whether or not the number of pair range candidates createdin the processing at S201 is greater than 2 (S241). When the number ofpair range candidates is not larger than 2 (no at S241), the CPU 1deletes all the pair range candidates (S248), ends the pair rangedetermination processing, and returns the processing to the collationprocessing shown in FIG. 25. As shown in a list 74 in FIG. 29, in thespecific example, the six pairs of the pair range candidates are created(yes at S241). In this case, the CPU 1 initializes an array of arotation angle of the image (S242). The CPU 1 initializes an array ofthe similarity degree (S243). The CPU 1 performs calculation processing(S244). In the calculation processing, the CPU 1 selects the two sets ofthe collation ridge information Vn and the registration ridgeinformation Rm for which the pair range candidate is identified, andidentifies, for each of the selected two sets of collation ridgeinformation and registration ridge information, both of ends when aplurality of base points inside the pair range candidate are connectedusing a line segment in accordance with the arrangement order. The CPU 1compares relative positions of both ends corresponding to each of thetwo pieces of collation ridge information and both ends corresponding toeach of the two pieces of registration ridge information, and calculatesthe similarity degree WR.

As shown in FIG. 31, in the calculation processing, from among the pairrange candidates stored in the list 74 in FIG. 29 by the pair rangecandidate selection processing at S201, the CPU 1 selects two sets ofthe collation pair range candidates (S251). The CPU 1 selects the pairrange candidates that include the six pairs of the base points Q1 to Q6in the ridge information V1 (the ridge Z1), and the pair rangecandidates that include the five pairs of the base points in the ridgeinformation V4 (the ridge Z4). For the two sets of collation ridgeinformation Vn selected by the processing at S251, the CPU 1 identifiesboth the ends when the plurality of base points inside the pair rangecandidate are connected in accordance with the arrangement order, andcalculates a length and angle of a start point line segment and an endpoint line segment when one of the ends is the start point and the otherend is the end point (S252). More specifically, of the base points Q1 toQ6 included in the pair range candidates of the ridge information V1 forthe ridge Z1 shown in the image 67 in FIG. 27 and in the list 74 in FIG.29, the CPU 1 takes the base point Q1 as the start point and takes thebase point Q6 as the end point. Of the base points Q19 to Q23 includedin the pair range candidates of the ridge information V4 for the ridgeZ4, the CPU 1 takes the base point Q19 as the start point and takes thebase point Q23 as the end point. For a start point line segment LS1connecting the base point Q1 and the base point Q19, the CPU 1calculates a length thereof, and an angle AS1 of the start point linesegment LS1 with respect to a line segment parallel to the X axis. Foran end point line segment LS2 that connects the base point Q6 and thebase point Q23, the CPU 1 calculates a length thereof, and an angle AS2of the end point line segment LS2 with respect to a line segmentparallel to the X axis.

For the two sets of collation ridge information Vn selected at S251, theCPU 1 calculates the length of a line segment obtained when theplurality of base points inside the pair range candidate are connectedin accordance with the arrangement order (S253). The length of a linesegment obtained when the base points Q1 to Q6 are connected in order isthe sum of distances d1 to d5. The length of a line segment obtainedwhen the base points Q19 to Q23 are connected in order is the sum ofdistances d19 to d22. The CPU 1 calculates a weighting, on the basis ofthe lengths of the start point line segment LS1 and the end point linesegment LS2 calculated at S252, and the length of the line segmentinside the pair range candidate calculated at S253 (S254). For example,the CPU 1 calculates, as the weighting, a value obtained by dividing thelength calculated at S253 by the sum of the length of the start pointline segment LS1 and the length of the end point line segment LS2obtained in the processing at S252. When the calculated weighting isequal to or greater than a predetermined value, the CPU 1 may substitutethe predetermined value for the weighting.

The CPU 1 refers to the list 74 shown in FIG. 29 and selects two sets ofthe registration pair range candidates corresponding to the two sets ofcollation pair range candidates selected at S251 (S255). By theprocessing at S251 and the processing at S255, the CPU 1 selects the twosets of registration ridge information and collation ridge information.Corresponding to the pair range candidate that includes the six pairs ofthe base points Q1 to Q6 in the ridge information V1 (the ridge Z1), theCPU 1 selects the pair range candidate that includes the six pairs ofthe base points P4 to P9 in the ridge information R2 (the ridge L2).Corresponding to the pair range candidate that includes the five pairsof the base points in the ridge information V4 (the ridge Z4), the CPU 1selects the pair range candidate that includes the five pairs of thebase points P21 to P25 in the ridge information R5 (the ridge L5).Similarly to S252, for the two sets of the registration ridgeinformation Rm selected by the processing at S256, the CPU 1 identifiesboth the ends when the plurality of base points inside the pair rangeare connected in accordance with the arrangement order, and calculates alength and angle of the start point line segment and the end point linesegment when one of the ends is taken as the start point and the otheris taken as the end point (S256). Of the base points P4 to P9 includedin the pair range candidates of the ridge information R2 for the ridgeL2, the base point P4 is the start point and the base point P9 is theend point. Of the base points P21 to P25 included in the pair rangecandidates of the ridge information R5 for the ridge L5, the CPU 1 takesthe base point P21 as the start point and takes the base point P25 asthe end point. For a start point line segment LT1 connecting the basepoint P4 and the base point P21, the CPU 1 calculates a length thereof,and an angle AT1 of the start point line segment LT1 with respect to aline segment parallel to the X axis. For an end point line segment LT2connecting the base point P9 and the base point P25, the CPU 1calculates a length thereof, and an angle AT2 of the end point linesegment LT2 with respect to a line segment parallel to the X axis.Similarly to S253, for the two sets of registration ridge information Rmselected at S255, the CPU 1 calculates the length of a line segmentobtained when the plurality of base points inside the pair rangecandidate are connected in accordance with the arrangement order (S257).The length of a line segment obtained when the base points P4 to P9 areconnected in order is the sum of distances D4 to D8. The length of aline segment obtained when the base points P21 to P25 are connected inorder is the sum of distances D21 to D24. The CPU 1 calculates aweighting, on the basis of the lengths of the start point line segmentLT1 and the end point line segment LT2 calculated at S256, and thelength of the line segment inside the pair range candidate calculated atS257 (S258). For example, the CPU 1 calculates, as the weighting, avalue obtained by dividing the length calculated at S257 by the sum ofthe length of the start point line segment LT1 and the length of the endpoint line segment LT2 obtained in the processing at S256. When thecalculated weighting is equal to or greater than a predetermined value,the CPU 1 may substitute the predetermined value for the weighting.

The CPU 1 calculates a degree of reliability, from the weightingcalculated by the processing at S254, and the weighting calculated atS258 (S259). When, among the selected two sets of the collation ridgeinformation Vn and the registration ridge information Rm, for at leastone of the two pieces of collation ridge information and the two piecesof registration ridge information, one of the two pieces of ridgeinformation is designated as first ridge information and the other isdesignated as second ridge information, the CPU 1 calculates the degreeof reliability using the length of one or more comparison line segmentsobtained by connecting at least one of the endpoints of both ends of thefirst ridge information and at least one of the endpoints of both endsof the second ridge information. The CPU 1 of the present embodimentcalculates, as the degree of reliability, the product of the weightingcalculated by the processing at S254 and the weighting calculated atS258. Using differences in distances, a difference in angle and thedegree of reliability calculated at S259, the CPU 1 calculates thesimilarity degree WR (S260). The differences in distances are adifference in the lengths of the collation start point line segmentcalculated at S253 and the length of the registration start point linesegment calculated at S256, and a difference in the lengths of thecollation end point line segment calculated at S253 and the registrationend point line segment calculated at S256. Specifically, the differencesin distances are the difference between the lengths of the line segmentsLS1 and LT1, and the difference between the lengths of the line segmentsLS2 and LT2. The difference in angle is a difference between an angle F1and an angle F2. The angle F1 is a difference in angle between acollation first line segment and a registration first line segment. Theangle F2 is a difference in angle between a collation second linesegment and a registration second line segment. In FIG. 27, of the pairrange candidates selected at S251, a line segment LS3 that connects thestart point and the end point of one of the pair range candidates is thecollation first line segment, and a line segment LS4 that connects thestart point and the end point of the other pair range candidate is thecollation second line segment. Of the pair range candidates selected atS255, a line segment LT3 that connects the start point and the end pointof one of the pair range candidates is the registration first linesegment, and a line segment LT4 that connects the start point and theend point of the other pair range candidate is the registration secondline segment. For example, the CPU 1 calculates the similarity degree WRthat is calculated on the basis of the ridge information, bysubstituting the differences in distances, the difference in angle, andthe degree of reliability calculated at S259 into a predeterminedformula. The similarity degree WR calculated at S258 indicates a greaterdegree of similarity the larger the value, and a lesser degree ofsimilarity the smaller the value.

The CPU 1 determines whether the similarity degree WR calculated by theprocessing at S260 is larger than a threshold value (S261). When thesimilarity degree WR is not larger than the threshold value (no atS261), the CPU 1 performs processing at S266 to be described later. Whenthe similarity degree WR calculated at S260 is larger than the thresholdvalue (yes at S261), the CPU 1 performs similarity degree calculationprocessing of the frequency information (S262). As shown in FIG. 32, inthe similarity degree calculation processing of the frequencyinformation, the CPU 1 sets the similarity degree WF of the frequencyinformation to zero (S281). The CPU 1 selects the start point of theselected collation pair range candidate and the start point of theselected registration pair range candidate (S282). The CPU 1 selects thebase point Q1 of the ridge information V1 (the ridge Z1), the base pointQ24 of the ridge information V5 (the ridge Z5), the base point P4 of theridge information R2 (the ridge L2), and the base point P27 of the ridgeinformation R6 (the ridge L6), as shown in FIG. 33. The CPU 1 determineswhether the frequency information is stored for the selected collationbase points Q1 and Q24 (S283). When the frequency information is notstored for at least one of the two collation base points (no at S283),the CPU 1 performs processing at S288 to be described later. Thefrequency information is stored for both the collation base points Q1and Q24 (yes at S283). In this case, the CPU 1 refers to the list 98shown in FIG. 22 and determines whether the frequency information isstored for the selected registration base points P4 and P27 (S284).

When the frequency information is not stored for at least one of the tworegistration base points (no at S284), the CPU 1 performs the processingat S288 to be described later. The frequency information is stored forboth the registration base points P4 and P27 (yes at S284). In thiscase, the CPU 1 calculates a distances dF of the frequency information,using the selected collation base points Q1 and Q24 and the selectedregistration base points P4 and P27 (S285). The CPU 1 calculates thedistance dF on the basis of a distance between the base point Q1 and thebase point P4, and a distance between the base point Q24 and the basepoint P27. The CPU 1 calculates a similarity degree wF from the distancedF calculated by the processing at S285 (S286). For example, the CPU 1calculates the similarity degree wF, by substituting the distances dFinto a predetermined formula. The CPU 1 adds the similarity degree wFcalculated at S286 to the similarity degree WF of the frequencyinformation, and updates the similarity degree WF of the frequencyinformation (S287). The CPU 1 determines whether all of the base pointsof the selected pair range candidate have been selected by theprocessing at S282 or processing at S289 (S288). When there is theunselected base point (no at S288), the CPU 1 selects the next basepoint in the arrangement_order (S289), and returns the processing toS283. When all of the base points of the selected pair range candidatehave been selected (yes at S288), the CPU 1 ends the similarity degreecalculation processing of the frequency information, and returns theprocessing to the calculation processing shown in FIG. 31.

After S262 shown in FIG. 31, the CPU 1 determines whether the similaritydegree WF of the frequency information calculated at S262 is larger thana threshold value (S263). When the similarity degree WF is not largerthan the threshold value (no at S263), the CPU 1 performs processingthat is similar to that of S266 of the third embodiment. When thesimilarity degree WF is larger than the threshold value (yes at S263),in an array of the similarity degrees, the CPU 1 stores each of the twocollation pair range candidates selected at S251 and the tworegistration pair range candidates selected at S255, as similaritydegree calculation pairs (S264). As shown in a list 75 in FIG. 33, theCPU 1 adds, to an array, the pair range candidates that include the sixpairs of the base points Q1 to Q6 in the ridge information V1 (the ridgeZ1), the pair range candidates that include the six pairs of the basepoints P4 to P9 in the ridge information R2 (the ridge L2), the pairrange candidates that include the five pairs of the base points Q19 toQ23 in the ridge information V4 (the ridge Z4), the pair rangecandidates that include the five pairs of the base points P21 to P25 inthe ridge information R5 (the ridge L5), and the similarity degrees WRand the similarity degrees WF of the frequency information calculated onthe basis of these pair range candidates. In the array of the rotationangles of the image, the CPU 1 stores a rotation angle of the imagecalculated from the collation start point line segment and end pointline segment calculated at S252, and the registration start point linesegment and end point line segment calculated at S256 (S265). As shownin the list 75 in FIG. 33, the CPU 1 adds, to the array of the rotationangle of the image, each of the difference between the registrationstart point line segment LT1 and the collation start point line segmentLS1 and the difference between the registration end point line segmentLT2 and the collation end point line segment LS2.

The CPU 1 determines whether or not all of the registration pair rangecandidates corresponding to the two collation pair range candidatesselected at S251 have been selected at S255 (S266). The processing atS266 is processing that takes into account a case in which the singlepair range candidate is associated with a plurality of the pair rangecandidates, as in the case of the pair range candidates for the ridgeinformation V5 (the ridge Z5) in the list 74 in FIG. 29. When some ofthe registration pair range candidates corresponding to the twocollation pair range candidates selected at S251 have not been selectedat S255 (no at S266), the CPU 1 returns the processing to S255. When allof the registration pair range candidates corresponding to the twocollation pair range candidates selected at S251 have been selected atS255 (yes at S266), the CPU 1 determines whether all of the combinationsof the collation pair range candidates selected by the processing atS201 have been selected in the processing at S251 (S267). In thespecific example, when, on the basis of the list 74 in FIG. 29, all ofthe ten combinations of the five collation pair range candidates havenot been selected in the processing at S251 (no at S267), the CPU 1returns the processing to S251. When all of the ten combinations of thefive collation pair range candidates have been selected in theprocessing at S251 (yes at S267), the CPU 1 ends the calculationprocessing and returns the processing to the pair range determinationprocessing shown in FIG. 30. As a result of the calculation processingshown in FIG. 31, the similarity degrees and the angles are stored for aplurality of similarity degree pairs, as in a list 76 shown in FIG. 33.

After S244 in FIG. 30, the CPU 1 determines whether a number of thesimilarity degrees WR (a number of the similarity degree pairs) added tothe array by the processing at S264 in FIG. 31 is larger than athreshold value (S245). When the number of the similarity degrees WR isnot larger than the threshold value (no at S245), the CPU 1 ends thepair range determination processing, and returns the processing to thecollation processing shown in FIG. 25. When the number of similaritydegrees WR is larger than the threshold value (yes at S245), the CPU 1performs pair range deletion processing (S246). The pair range deletionprocessing is processing that determines the pair range to be used incalculation of a similarity degree of pair ranges that satisfypredetermined conditions, by deleting the similarity degree calculationpairs that do not satisfy the predetermined conditions from among thesimilarity degree calculation pairs selected by the pair range candidateselection processing at S201 and stored at S264 of the calculationprocessing at S244. Specifically, as shown in FIG. 34, in the pair rangedeletion processing, the CPU 1 calculates an average value M and astandard deviation H of the angles added to the array by the processingat S265 in FIG. 31 (S271). The CPU 1 selects one of the angles among theangles stored at S265 (S272). The CPU 1 determines whether an absolutevalue of a difference between the angle selected at S272 and the averagevalue M of the angles calculated at S271 is larger than the standarddeviation H (S273). When the absolute value of the difference with theaverage value M of the angles calculated at S271 is larger than thestandard deviation H (yes at S273), the CPU 1 deletes the pair rangecandidate, the similarity degree WR and the angle corresponding to theangle selected at S272, from the array (S274). When the absolute valueof the difference with the average value M of the angles calculated atS271 is not larger than the standard deviation H (no at S273), or afterthe processing at S274, the CPU 1 determines whether all the anglesadded to the array at S265 have been selected by the processing at S272(S275). When there is the angle that has not been selected by theprocessing at S272 (no at S275), the CPU 1 returns the processing toS272. When all of the angles have been selected by the processing atS272 (yes at S275), and when, of the similarity degree calculation pairsstored by the processing at S264, a plurality of pair range candidatesare stored for one of the two sets of collation pair range candidates orthe two sets of registration pair range candidates, the CPU 1 selectsthe two sets of pair range candidates from the plurality of pair rangecandidates (S276). For example, as shown in the list 76 in FIG. 33, withrespect to the pair range candidates set in the collation ridgeinformation V1 (the ridge Z1), the similarity degrees WR are calculatedtaking the pair range candidates set in each of the collation ridgeinformation V2 to V5 as similarity degree calculation pairs. Forexample, from among the pair range candidates set in each of thecollation ridge information V2 to V5, the CPU 1 selects the pair rangecandidate set in the ridge information V2 of a similarity degreecalculation pair 77 and the pair range candidate set in the ridgeinformation V3 of a similarity degree calculation pair 78.

Of the similarity degree calculation pairs selected by the processing atS276, the CPU 1 determines whether line segments obtained when theplurality of base points are connected in accordance with thearrangement order are partially overlapping (S277). In the case of thepair range candidate set in the ridge information V2, and the pair rangecandidate set in the ridge information V3, line segments from the basepoints Q7 to Q9 are overlapping (yes at S277). In this case, of thesimilarity degree calculation pairs 77 and 78, the CPU 1 deletes thepair for which the similarity degree is smaller (S278). When thesimilarity degree calculation pairs selected at S276 are not overlapping(no at S277), or after S278, the CPU 1 determines whether all of thesimilarity degree calculation pairs have been selected by the processingat S276 (S279). When one of the combinations has not been selected bythe processing at S276 (no at S279), the CPU 1 returns the processing toS276. When all of the combinations of the similarity degree calculationpairs have been selected by the processing at S276 (yes at S279), theCPU 1 ends the pair range deletion processing, and returns theprocessing to the pair range determination processing shown in FIG. 30.After the processing at S246, the CPU 1 ends the pair rangedetermination processing, and returns the processing to the collationprocessing shown in FIG. 25.

After S202 shown in FIG. 25, the CPU 1 calculates a score SC, using thesum of the similarity degrees WR calculated at S260 that have not beendeleted by the pair range deletion processing shown in FIG. 34 and thesum of the similarity degrees WF frequency information of the (S203).The score SC indicates a similarity degree between the collation ridgeinformation and frequency information, and the registration ridgeinformation and frequency information. For example, the CPU 1 calculatesthe score SC by substituting the sum of the similarity degree WR and asimilarity degree WF into a predetermined formula. The score SC of thepresent embodiment indicates a greater similarity degree between thecollation ridge information Vn and the frequency information, and theregistration ridge information Rm and the frequency information thelarger the value, and indicates a lesser similarity degree the smallerthe value. The CPU 1 determines whether the score SC calculated at S203is larger than a threshold value (S204). When the score SC is largerthan the threshold value (yes at S204), the CPU 1 sets “Success” as anauthentication result of the skin authentication (S205). When the scoreSC is not larger than the threshold value (no at S204), the CPU 1 sets“Failure” as the authentication result of the skin authentication(S206). In the processing at S205 and S206, the CPU 1 may performnotification as necessary by displaying the authentication result on thedisplay portion 6 or the like. The CPU 1 ends the collation processingand returns the processing to the skin authentication processing shownin FIG. 8. After S15 in FIG. 8, the CPU 1 ends the skin authenticationprocessing.

Evaluation Test

An evaluation test was conducted, using the ridge information for theskin authentication, to verify whether the authentication performanceimproves. For each of conditions 1 to 6 to be described below, anoptical touch sensor was used to acquire 5 to 10 images per finger of 31fingers, each being an image of 2000 dpi having 480 pixels in thehorizontal direction and 800 pixels in the vertical direction. One ofthe images was used as a registration image and another of the imageswas used as a collation image, and receiver operating characteristics(ROC) were calculated. Condition 1 is a condition to perform the skinauthentication using a known minutia method. Condition 2 is a conditionto perform the skin authentication using the ridge information of thethird embodiment. Condition 3 is a condition to perform the skinauthentication using both the minutia method and the ridge information.Condition 4 is a condition to perform the skin authentication using thefrequency information showing the changes in color around a featurepoint extracted using the minutia method. Condition 5 is a condition toperform the skin authentication using the frequency information showingan area surrounding the base point representing the sweat pore.Condition 6 is a condition to perform the skin authentication bycombining Condition 5 and Condition 6. Each of Conditions 1 to 6 areshown by results 31 to 36 in FIG. 35. As shown in FIG. 35, whenConditions 1 to 3 are compared, in comparison to Condition 1, Condition3 shows a superior authentication performance. From this, it wasverified that the ridge information can improve the authenticationperformance of a known authentication method. In comparison to Condition4, Condition 6 shows a superior authentication performance. From this,it was verified that the frequency information showing the changes inthe color surrounding the sweat pore can improve the authenticationperformance of the known authentication method.

The skin information processing device 10 can generate the frequencyinformation showing the changes in color around the base point, when thesweat pore on the ridge of the skin in the image is used as the basepoint. The arrangement of sweat pores on the ridges of the skin isunique, in the same way as a fingerprint or a voiceprint, and is saidnot to change over the period of a whole lifetime. Even when the size ofthe image that represents the skin information is smaller than in therelated art, and the branch points and endpoints of the ridges are notincluded in the image, there is a possibility that a plurality of thesweat pores can be acquired. The skin information processing device 10can generate the frequency information that is able to cancel out aninfluence of the base point rotating or moving with respect to areference, when using the base point representing the characteristicsweat pore as the biometric information. In other words, even when thesize of the image representing the skin information is smaller than inthe related art, the skin information processing device 10 can generatethe information that is not easily influenced by acquisition conditionsof the biometric information,

The skin information processing device 10 extracts the plurality of basepoints arranged on the same continuous ridge, from among the pluralityof base points determined by the processing at S23 (S65), and generatesthe position information of each of the extracted plurality of basepoints, and the ridge information that includes the arrangement order ofthe plurality of identified base points on the ridge (S72). The skininformation processing device 10 associates the ridge informationgenerated at S72 with the frequency information, and stores theassociated information in the RAM 3 (the storage portion) as theinformation to be used in the skin authentication (S28). Thus, the skininformation processing device 10 can generate the ridge information andstore the ridge information and the frequency information in associationwith each other. The ridge information includes the position informationindicating the position, in the image, of each of the plurality of basepoints arranged on the same continuous ridge, and the arrangement orderof the plurality of base points on the ridge. The base point representsthe sweat pore on the ridge. When the plurality of base points areconnected by the line segment in order in accordance with thearrangement order, a plurality of the line segments connecting theplurality of base points form the shape of the ridge as a whole. Alength of each of the line segments represents a distance between theadjacent base points arranged on the same continuous ridge.Specifically, the ridge information is information representing theshape of the ridge using the arrangement of the sweat pores, and it canbe said that it is information that emphasizes characteristic sectionsof the biometric information represented by the image. Thus, in additionto the frequency information generated on the basis of the base points,the skin information processing device 10 can generate the ridgeinformation that is the information used in the skin authentication andthat contributes to an improvement in authentication performance, incomparison to the related art.

For each of the plurality of base points extracted by the processing atS65, the skin information processing device 10 calculates the relativeangle of the line segment connecting the base point with the precedingbase point in the arrangement order on the ridge with respect to theline segment connecting the base point with the next base point in thearrangement order (S116). For the plurality of reference points on thecircumference of the circle whose center is the base point determined bythe processing at S23 and whose radius is the predetermined value, theskin information processing device 10 takes, as the starting point, thepoint determined on the basis of the base point and the relative anglescalculated at S115 and S119 with respect to the base point. Then, foreach of the plurality of reference points acquired in order inaccordance with the predetermined conditions, the skin informationprocessing device 10 acquires, as the sample information, informationthat associates the color information corresponding to the referencepoint with reference position information corresponding to the positionof the reference point on the image (S116). The skin informationprocessing device 10 calculates the frequency components of the changesin the color information with respect to the reference positioninformation acquired at S116 and S120, respectively, using a linearprediction coefficient which is calculated without multiplying a windowfunction, and generates the frequency information (S117, S121). The skininformation processing device 10 generates the ridge information thatincludes the position information of each of the plurality of basepoints, the arrangement order of the plurality of identified base pointson the ridge, and the relative angles. Thus, at S116 and S120, the skininformation processing device 10 can determine the acquisition startingpoint using the arrangement of the base points on the same continuousridge. The skin information processing device 10 can generate the ridgeinformation that includes the relative angles. Since the ridgeinformation includes the relative angles, when performing the skinauthentication using the ridge information, the skin informationprocessing device 10 does not need to newly calculate the relativeangles between the base points. In other words, the skin informationprocessing device 10 can shorten an authentication time when performingthe skin authentication. By generating the ridge information thatincludes the relative angles, the skin information processing device 10can calculate the similarity degree while taking into account aninfluence of angle in a case in which, when the skin authentication isperformed, an image is acquired under an angle condition different fromthat at the time of registration.

The skin information processing device 10 determines the positionalcorrespondence that is the correspondence between the base point of thecollation ridge information used in the skin authentication at S201 andS202, and the base point of the registration ridge information stored inthe DB 28. On the basis of the determined positional correspondence, theskin information processing device 10 calculates the score SC that isthe similarity degree between the collation ridge information andfrequency information, and the registration ridge information andfrequency information (S262). The skin information processing device 10can compare the frequency information for collation and the frequencyinformation for registration, and calculate the similarity degreebetween them, while taking into account an influence of the informationrepresented by the image rotating or moving with respect to thereference, when using the base point representing the characteristicsweat pore as the skin information. In other words, when the skininformation processing program is executed, a computer can appropriatelycalculate the score SC on the basis of collation information that is noteasily influenced by the acquisition conditions of the skin information,even when the size of the image representing the skin information issmaller than in the related art.

The skin information processing device 10 determines the area centroidof the sweat pore in the image as the base point, and uses the areacentroid as the position information of the base point. The skininformation processing device 10 can determine the area centroid of thesweat pore, which represents features of the shape and size of the sweatpore, as the base point, and can generate the ridge information.

The skin information processing device 10 calculates the distance fromthe base point to the next base point in the arrangement order (S34),and generates the ridge information that includes the positioninformation of each of the plurality of base points on the samecontinuous ridge, and the arrangement order and distances of theidentified base points on the ridge (S72). The skin informationprocessing device 10 can generate the ridge information that includesthe distance to the next base point in the arrangement order. The ridgeinformation includes the distance to the next base point in thearrangement order, and thus, when the ridge information is used toperform the skin authentication, with respect to the registration ridgeinformation, it is not necessary to newly calculate the distancesbetween the base points. The skin information processing device 10 cangenerate the ridge information that includes the distance to the nextbase point in the arrangement order, and thus, the similarity degree canbe calculated while taking into account an influence of position, in acase in which, when the skin authentication is performed, an image isacquired under a position condition that is different from that at thetime of registration.

The skin information processing device 10 calculates, for each of theplurality of base points on the same continuous ridge, the relativeangle between the line segment connecting the base point with thepreceding base point in the arrangement order and the line segmentconnecting the base point with the next base point in the arrangementorder (S82). For each of the plurality of base points on the samecontinuous ridge, the skin information processing device 10 generatesthe ridge information that includes the position information, and thearrangement order and the relative angles of the identified base pointson the ridge (S72). The skin information processing device 10 generatesthe ridge information that includes the relative angles, and thus, whenthe ridge information is used to perform the skin authentication, acomputer does not need to newly calculate the relative angles betweenthe base points. The skin information processing device 10 can shortenan authentication time at the time of the skin authentication. Bygenerating the ridge information that includes the relative angles, theskin information processing device 10 can calculate the similaritydegree while taking into account an influence of angle in a case inwhich, when the skin authentication is performed, an image is acquiredunder an angle condition that is different from that at the time ofregistration.

When each of the plurality of base points is taken as the target basepoint, the skin information processing device 10 generates, as theconnection information, the information that associates the positioninformation of the target base point with the position information ofthe connection base point, which is the base point that is disposed onthe same continuous ridge as the target base point, and that precedes orfollows the target base point in the arrangement order on the samecontinuous ridge (S25). On the basis of the connection informationgenerated at S25, the skin information processing device 10 extracts theplurality of base points arranged on the same continuous ridge (S65). Incomparison to when the processing at S25 is not performed, the skininformation processing device 10 can more appropriately generate theridge information through simpler processing.

On the basis of the connection information generated by the processingat S25, the skin information processing device 10 identifies, of theplurality of base points, the base point for which the number ofpreceding or following base points in the arrangement order is 1, as thestart point that is the first base point in the arrangement order or asthe end point that is the last base point in the arrangement order. Theskin information processing device 10 identifies, of the plurality ofbase points, the base point for which the number of preceding andfollowing base points is three or more, as the branch point of theridge. When the continuous ridge does not include the branch point, theskin information processing device 10 defines the ridge that does nothave the bifurcation from the start point to the end point, extracts theplurality of base points arranged on the defined ridge, and generatesthe ridge information. When the continuous ridge includes the branchpoint, the skin information processing device 10 defines the pluralityof ridges without the bifurcation from the start point to the end pointincluding the branch point, the number of ridges corresponding to thenumber of bifurcations at the branch point. For each of the definedplurality of ridges, the plurality of base points arranged on the sameridge are extracted and the ridge information is generated. Thus, whenthe branch point is included on the same continuous ridge, the skininformation processing device 10 defines the plurality of ridges withoutthe bifurcation from the start point to the end point, from the samecontinuous ridge that includes the branch point, and thus, the ridgeinformation can be generated in which all of the ridges can be treatedas the ridges that do not include the branch point.

The skin information processing device 10 determines the positionalcorrespondence that is the correspondence between the base point of thecollation ridge information used in the skin authentication, and thebase point of the registration ridge information stored in the DB 28(S201 and S202 in FIG. 25). On the basis of the determined positionalcorrespondence, the skin information processing device 10 calculates thesimilarity degree WR between the collation ridge information and theregistration ridge information (S260), and calculates the score SC usingthe calculated similarity degree WR (S203). Thus, the skin informationprocessing device 10 uses the ridge information which represents theshape of the ridge using the arrangement of the sweat pores and in whichthe feature points of the biometric information represented by the imageare emphasized. Thus, in comparison to a case in which the relativepositions of the sweat pores are simply compared, the processing can beperformed with a higher degree of reliability in the determination ofthe positional correspondence and the calculation of the similaritydegree.

In the processing at S201 and S202 shown in FIG. 25, from the pluralityof combinations of the collation ridge information and registrationridge information, the skin information processing device 10 identifiesthe pair ranges for which the difference between the selected collationridge information and the selected registration ridge information isequal to or less than the threshold value for the base points over apredetermined continuous number of base points, and then determines thepositional correspondence. Thus, the skin information processing device10 can determine the positional correspondence using relatively simpleprocessing.

The skin information processing device 10 selects two sets of thecollation ridge information and registration ridge information for whichthe pair range candidate has been identified (S251, S255). For each ofthe two selected sets of the collation ridge information andregistration ridge information, the skin information processing device10 identifies both the ends of the line segment obtained by connectingthe plurality of base points in the pair range in accordance with thearrangement order, compares both the ends respectively corresponding tothe two pieces of collation ridge information with both the endsrespectively corresponding to the two pieces of registration ridgeinformation, and calculates the score SC (S254, S258, S259, S260, andS203). By comparing both the ends of the ridge information in the pairranges, the skin information processing device 10 can efficientlycompare the collation ridge information and the registration ridgeinformation and calculate the similarity degree.

When, among the two sets of the collation ridge information and theregistration ridge information selected by the processing at S251 andS255, for at least one of the two pieces of collation ridge informationand the two pieces of registration ridge information, one of the twopieces of ridge information is designated as the first ridge informationand the other is designated as the second ridge information, the skininformation processing device 10 calculates the degree of reliabilityusing the length of one or more of the comparison line segments obtainedby connecting at least one of the endpoints of both ends of the firstridge information and at least one of the endpoints of both ends of thesecond ridge information (S259). The skin information processing device10 calculates the similarity degree WR by multiplying a comparisonresult of the relative positions by the degree of reliability, andcalculates the score SC using the calculated similarity degree WR(S260). In comparison to a case in which the similarity degree WR iscalculated without using the degree of reliability, the skin informationprocessing device 10 can calculate the similarity degree offering a highdegree of authentication accuracy.

The skin information processing device and the non-transitorycomputer-readable medium according to the present disclosure is notlimited to the embodiments described above, and various types ofmodifications may be made insofar as they are within the scope of thepresent disclosure. For example, the modifications (A) to (C) describedbelow may be made as desired.

(A) The configuration of the skin information processing device 10 maybe changed as appropriate. For example, the skin information processingdevice 10 is not limited to a smart phone, and may be a mobile device,such as a notebook PC, a tablet PC or a mobile telephone, for example,or may be a device such as an automated teller machine (ATM) or anentrance and exit management device. The skin information acquisitiondevice 8 may be provided separately from the skin information processingdevice 10. In this case, the skin information acquisition device 8 andthe skin information processing device 10 may be connected by aconnection cable, or may be wirelessly connected, such as with Bluetooth(registered trademark) or near field communication (NFC). The detectionmethod of the skin information acquisition device 8 is not limited tothe capacitance method, and may be another method (for example, anelectric field method, a pressure method, or an optical method). Theskin information acquisition device 8 is not limited to the surfacetype, and may be a linear type. The size, the color information and theresolution of the image generated by the skin information acquisitiondevice 8 may be changed as appropriate. Therefore, for example, thecolor information may be information corresponding to a color image, aswell as information corresponding to a white and black image.

(B) The skin information processing program may be stored in a storagedevice of the skin information processing device 10 before the skininformation processing device 10 executes the programs. Therefore, themethods by which the information processing programs are acquired, theroutes by which they are acquired, and the device in which the programsare stored may each be modified as desired. The skin informationprocessing programs, which are executed by the processor of the skininformation processing device 10, may be received from another devicethrough one of a cable and wireless communications, and they may bestored in a storage device such as a flash memory or the like. The otherdevice may be, for example, a personal computer (PC) or a server that isconnected through a network.

(C) The individual steps in the skin information processing may notnecessarily be performed by the CPU 1, and some or all of the steps mayalso be performed by another electronic device (for example, an ASIC).The individual steps of the skin information processing may also beperformed by distributed processing among a plurality of electronicdevices (for example, a plurality of CPUs). The order of the individualsteps in the collation information processing can be modified asnecessary, and steps can be omitted and added. A case in which anoperating system (OS) or the like that is operating in the skininformation processing device 10 performs some or all of the actualprocessing, based on commands from the CPU 1 of the skin informationprocessing device 10, and the functions of the embodiment that isdescribed above are implemented by that processing, falls within thescope of the present disclosure. The modifications hereinafter describedin paragraphs (C-1) to (C-8) may also be applied to the main processingas desired.

(C-1) Pre-processing may be performed, as appropriate, on the imageacquired at S11. For example, filtering processing may be performed inorder to remove high frequency components of the image as noise. As aresult of performing the filtering processing, gradation changes in edgeportions of the image become moderate. One of a known low pass filter, aGaussian filter, a moving average filter, a median filter and anaveraging filter may be used as a filter used for the filteringprocessing. In another example, the filtering processing to extractspecific frequency band components only may be performed on the imageacquired at S11. A band including a ridge and trough period of thefingerprint may be selected as the specific frequency band. In thiscase, a known band-pass filter can be taken as an example of the filterused for the filtering processing.

(C-2) As long as the base point is a point that represents the sweatpore, the base point need not necessarily be the area centroid of thesweat pore. It is sufficient that the ridge information include at leastthe position information of the base points and the arrangement order ofthe base points on the ridge. The arrangement order may be indicated bya storage order of the position information. The ridge information mayinclude, as the angle of the base point, the orientation of the vectorfrom the base point toward the preceding base point in the arrangementorder, and the orientation of the vector from the base point to thefollowing base point in the arrangement order. The ridge informationneed not necessarily define the ridge without the bifurcation, when thebranch point is included in the base points on the same continuousridge. For example, the ridge information including the bifurcation, asshown in the ridge information R3 in FIG. 27, may be defined. The ridgeinformation need not necessarily be generated on the basis of theconnection information. The processing to generate the connectioninformation may be omitted as necessary.

(C-3) When determining the positional correspondence that is thecorrespondence between the base points of the collation ridgeinformation used in the skin authentication, and the base points of theregistration ridge information stored in the DB 28, the skin informationprocessing device may determine the positional correspondence whiletaking partially missing sweat pores into account. For example, a caseis assumed in which, when comparing the registration ridge informationR1 to R5 shown in the image 47 and the collation ridge information V1 toV4 shown in the image 67 in FIG. 27, the base point P26 in the collationridge information V4 is missing. In this case, in the processing of theabove-described embodiments, after comparing the base point Q25 of theridge information V4 and a base point P28 of the ridge information R5,the base point Q27 of the ridge information V4 and a base point P29 ofthe ridge information R5 are compared. Even if it is determined, on thebasis of the distances and relative angles, that the base point Q27 andthe base point P29 are not similar, if it is determined that the basepoint Q27 is similar to the base point P28, on the basis of the distanceof the base point P30, which follows the base point P27 in thearrangement order, from the base point P28 and the relative angle, thepair range may be set while passing over the base point P29.

(C-4) The calculation method of the degree of reliability may be changedas appropriate. The degree of reliability may be calculated byidentifying, for each of the two sets of collation ridge information andregistration ridge information for which the pair range is identified,both the ends of the line segment obtained when the plurality of basepoints in the pair range are connected in accordance with thearrangement order, and comparing both the ends respectivelycorresponding to the two pieces of collation ridge information with boththe ends respectively corresponding to the two pieces of registrationridge information. Thus, the degree of reliability may be calculatedusing the following procedure, for example. From the two pieces ofcollation ridge information, a first line segment and a second linesegment are defined that are obtained when the base points in the setpair range are connected in accordance with the arrangement order. Bothends of the first line segment are a first start point and a first endpoint, and both ends of the second line segment are a second start pointand a second end point. A line segment obtained when the first startpint and the second start point are connected is a first comparison linesegment. A line segment obtained when the first end point and the secondend point are connected is a second comparison line segment. A linesegment obtained when the first start point and the second end point areconnected is a third comparison line segment. A line segment obtainedwhen the first end point and the second start point are connected is afourth comparison line segment. The degree of reliability may becalculated on the basis of at least one of the first to fourthcomparison line segments. For example, the degree of reliability may becalculated using only the first comparison line segment, or the degreeof reliability may be calculated using the first to fourth comparisonline segments in combination.

(C-5) The collation information including at least one of the generatedconnection information and the ridge information need not necessarily beused in the processing to calculate the information similarity degree.The skin authentication may be performed in combination with knowncollation information. For example, a final determination may be made bycombining a collation result from a known minutia method and a collationresult using the collation information method of the present disclosure.If this is done, the collation is performed from diverse viewpoints, andit is expected that the collation accuracy will improve. Further, aconfiguration may be adopted in which the collation method can beautomatically set or set by the user, from among a plurality of types ofcollation method, while taking account of processing time andauthentication accuracy and the like.

(C-6) It is sufficient that the frequency information be

information showing changes in the color around the base point. Forexample, the frequency components are not limited to the one-dimensionalgroup delay spectrum. For example, other known frequency components,such as an LPC spectrum, a group delay spectrum, an LPC cepstrum, acepstrum, an autocorrelation function, a cross correlation function andthe like may be used as the frequency components. The frequencyinformation need not necessarily be associated with the ridgeinformation. The frequency information may be associated with theconnection information. The processing to calculate the frequencyinformation may be omitted.

(C-7) The calculation method of the frequency information may be changedas appropriate. For example, when the one-dimensional group delayspectrum is used as the frequency components as in the above-describedembodiments, noise components sometimes appear strongly in highfrequency components. Taking this type of case into account, thefrequency information may be selected on the basis of frequencyinformation that includes a predetermined number of components selectedwhile prioritizing lower order components. The predetermined number maybe set in advance while taking into account a number of samples,authentication accuracy and the like. For example, when the number ofsamples N acquired for a single first reference point is 128, thepredetermined number is set to a value from 10 to 63. Preferably, thepredetermined number is set to be a value between 12 to 20. When thenumber of samples is N, the predetermined number is preferably set to avalue from (number of samples N/10) to (number of samples N/5). Forexample, the frequency information may be calculated using a windowfunction.

(C-8) The acquisition method of the samples may be changed asappropriate. The samples may be acquired using a direction indicating afeature in the changes in the color information around the base point. Acurvature of the changes in the color information around the base pointmay be calculated as part or all of a reference direction. The curvaturerefers to an amount indicating a degree of curvature of a curved line.Various setting values set in the collation information processing,threshold values, and the like may be changed as appropriate. For thevarious setting values, threshold values, and the like, a plurality oftypes may be set depending on acquisition conditions of the base point(a number, a surface area, and a shape of the sweat pores, and so on).

The apparatus and methods described above with reference to the variousembodiments are merely examples. It goes without saying that they arenot confined to the depicted embodiments. While various features havebeen described in conjunction with the examples outlined above, variousalternatives, modifications, variations, and/or improvements of thosefeatures and/or examples may be possible. Accordingly, the examples, asset forth above, are intended to be illustrative. Various changes may bemade without departing from the broad spirit and scope of the underlyingprinciples.

What is claimed is:
 1. A skin information processing method for a skininformation processing device comprising a storage portion, the skininformation processing method comprising: acquiring an image;determining a base point representing a sweat pore on a ridge of skin,from the acquired image and acquiring position information correspondingto a position of the base point on the image; acquiring sampleinformation indicating changes in color information around thedetermined base point; generating, as frequency information, informationassociating frequency components of the acquired sample information withthe position information; and causing the storage portion to storeinformation including the generated frequency information and theposition information of the base point, as information used in skinauthentication.
 2. The skin information processing method according toclaim 1, further comprising: extracting, from among a plurality of thebase points, a plurality of the base points disposed on a samecontinuous ridge; and generating ridge information including theposition information of each of the plurality of extracted base points,and an arrangement order of the plurality of extracted base points onthe ridge, and wherein the causing the storage portion to storeinformation includes causing the storage portion to store the generatedridge information and the frequency information, in association witheach other, as the information used in the skin authentication.
 3. Theskin information processing method according to claim 2, furthercomprising: calculating, for each of the plurality of extracted basepoints, a relative angle of a line segment connecting the base point anda following base point in the arrangement order with respect to a linesegment connecting the base point and a preceding base point in thearrangement order, and wherein: the acquiring the sample informationincludes acquiring, as the sample information, information associatingcolor information corresponding to a reference point with referenceposition information corresponding to a position of the reference pointon the image, for each of a plurality of the reference points, theplurality of reference points being on a circumference of a circle whosecenter is the determined base point and whose radius is a predeterminedvalue, and the plurality of reference points being acquired sequentiallyin accordance with a predetermined condition from a starting pointdetermined on the basis of the base point and the calculated relativeangle, the generating the frequency information includes calculatingfrequency components of changes in the color information with respect tothe reference position information for the acquired sample information,using a linear prediction coefficient calculated without multiplying awindow function, and generating the frequency information, and thegenerating the ridge information includes generating the positioninformation of each of the plurality of extracted base points, thearrangement order of the extracted plurality of base points on theridge, and the relative angle.
 4. The skin information processing methodaccording to claim 1, further comprising: determining a positionalcorrespondence, which is a correspondence between the base point of theridge information for collation that is used in the skin authenticationand the base point of the ridge information for registration that isstored in the storage portion; and calculating, on the basis of thepositional correspondence determined in the correspondence determining,an information similarity degree, the information similarity degreebeing a similarity degree between the ridge information and thefrequency information for collation and the ridge information and thefrequency information for registration.
 5. A skin information processingdevice, comprising: a processor; a storage portion; and a memoryconfigured to store computer-readable instructions that, when executedby the processor, instruct the processor to perform processescomprising: acquiring an image; determining a base point that representsa sweat pore on a ridge of skin, from the acquired image and acquiringposition information corresponding to a position of the base point onthe image; acquiring sample information indicating changes in colorinformation around the determined base point; generating, as frequencyinformation, information associating frequency components of theacquired sample information with the position information; and causingthe storage portion to store information including the generatedfrequency information and the position information of the base point, asinformation used in skin authentication.
 6. The skin informationprocessing device according to claim 5, wherein the computer-readableinstructions further instruct the processor to perform processescomprising: extracting, from among a plurality of the base points, aplurality of the base points disposed on a same continuous ridge; andgenerating ridge information including the position information of eachof the plurality of extracting base points, and an arrangement order ofthe plurality of extracted base points on the ridge, and the causing thestorage portion to store information includes causing the storageportion to store the generated ridge information and the frequencyinformation, in association with each other, as the information used inthe skin authentication.
 7. The skin information processing deviceaccording to claim 6, wherein the computer-readable instructions furtherinstruct the processor to perform a process comprising: calculating, foreach of the plurality of extracted base points, a relative angle of aline segment connecting the base point and a following base point in thearrangement order with respect to a line segment connecting the basepoint and a preceding base point in the arrangement order, the acquiringthe sample information includes acquiring, as the sample information,information associating color information corresponding to a referencepoint with reference position information corresponding to a position ofthe reference point on the image, for each of a plurality of thereference points, the plurality of reference points being on acircumference of a circle whose center is the determined base point andwhose radius is a predetermined value, and the plurality of referencepoints being acquired sequentially in accordance with a predeterminedcondition from a starting point determined on the basis of the basepoint and the calculated relative angle, the generating the frequencyinformation includes calculating frequency components of changes in thecolor information with respect to the reference position information forthe acquired sample information, using a linear prediction coefficientcalculated without multiplying a window function, and generating thefrequency information, and the generating the ridge information includesgenerating the position information of each of the plurality ofextracted base points, the arrangement order of the extracted pluralityof base points on the ridge, and the relative angle.
 8. The skininformation processing device according to claim 5, wherein thecomputer-readable instructions further instruct the processor to performprocesses comprising: determining a positional correspondence, which isa correspondence between the base point of the ridge information forcollation that is used in the skin authentication and the base point ofthe ridge information for registration that is stored in the storageportion; and calculating, on the basis of the positional correspondencedetermined in the correspondence determining, an information similaritydegree, the information similarity degree being a similarity degreebetween the ridge information and the frequency information forcollation and the ridge information and the frequency information forregistration.
 9. A non-transitory computer-readable medium storingcomputer-readable instructions that are executed by a processor providedin a skin information processing device comprising a storage portion,the computer-readable instructions, when executed, instructing theprocessor to perform processes comprising: acquiring an image;determining a base point representing a sweat pore on a ridge of skin,from the acquired image and acquiring position information correspondingto a position of the base point on the image; acquiring sampleinformation indicating changes in color information around thedetermined base point; generating, as frequency information, informationassociating frequency components of the acquired sample information withthe position information; and causing the storage portion to storeinformation including the generated frequency information and theposition information of the base point, as information used in skinauthentication.
 10. The non-transitory computer-readable mediumaccording to claim 9, wherein the computer-readable instructions furtherinstruct the processor to perform processes comprising: extracting, fromamong a plurality of the base points, a plurality of the base pointsdisposed on a same continuous ridge; and generating ridge informationincluding the position information of each of the plurality of extractedbase points, and an arrangement order of the plurality of extracted basepoints on the ridge, and the causing the storage portion to storeinformation includes causing the storage portion to store the generatedridge information and the frequency information, in association witheach other, as the information used in the skin authentication.
 11. Thenon-transitory computer-readable medium according to claim 10, whereinthe computer-readable instructions further instruct the processor toperform a process comprising: calculating, for each of the plurality ofextracted base points, a relative angle of a line segment connecting thebase point and a following base point in the arrangement order withrespect to a line segment connecting the base point and a preceding basepoint in the arrangement order, the acquiring the sample informationincludes acquiring, as the sample information, information associatingcolor information corresponding to a reference point with referenceposition information corresponding to a position of the reference pointon the image, for each of a plurality of the reference points, theplurality of reference points being on a circumference of a circle whosecenter is the determined base point and whose radius is a predeterminedvalue, and the plurality of reference points being acquired sequentiallyin accordance with a predetermined condition from a starting pointdetermined on the basis of the base point and the calculated relativeangle, the generating the frequency information includes calculatingfrequency components of changes in the color information with respect tothe reference position information for the acquired sample information,using a linear prediction coefficient calculated without multiplying awindow function, and generating the frequency information, and thegenerating the ridge information includes generating the positioninformation of each of the plurality of extracted base points, thearrangement order of the extracted plurality of base points on theridge, and the relative angle.
 12. The non-transitory computer-readablemedium according to claim 9, wherein the computer-readable instructionsfurther instruct the processor to perform processes comprising:determining a positional correspondence, which is a correspondencebetween the base point of the ridge information for collation that isused in the skin authentication and the base point of the ridgeinformation for registration that is stored in the storage portion; andcalculating, on the basis of the positional correspondence determined inthe correspondence determining, an information similarity degree, theinformation similarity degree being a similarity degree between theridge information and the frequency information for collation and theridge information and the frequency information for registration.